DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Status and Formal Matters
The instant action is in response to papers filed 11/17/2025.
Applicant’s election without traverse of 1. the human subject has received an initial treatment (claim 21); 2. endocrine therapy (claims 21 and 32); 3. the subject has a high risk of recurrence, the subject is treated with the adjuvant therapy for more than 5 years after the initial treatment (claim 21); 4. distant cancer recurrence (claim 27); and 5. tamoxifen (claim 29). in the reply filed on 1/2/2024 is acknowledged.
Claim 28 withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected species, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 1/2/2024.
Claims 21, 23-30, 32-33 are pending.
Claims 21, 23-27, 29-30, 32-33 are being examined.
The previous objection to the specification has been withdrawn in view of the amendment to the claims.
Priority
The instant application was filed 10/28/2021 and is a continuation of 14483108 , filed 09/10/2014,and claims priority from provisional application 61876757, filed 09/11/2013.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 21, 22-27, 29-30, 32-33 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Independent claim 21 and 32 have been amended to provide the steps of calculating a BCI dataset of human subjects, selecting a BCI cutoff and then calculating a BCI for from a breast cancer cell sample, then treating. Thus the claims as presented are drawn to a method of experimenting, analyzing, and treating. The instant response asserts support for the amendment can be found on pages 2-3, 10-11 and 31. These arguments have been thoroughly reviewed but are not considered persuasive as the cited portions generally support steps (c ) I, ii, iii, iv, d, e and f, but do not provide any indication disclosure views the initial investigation as cancer patients as part of the invention. Further the specification and initially filed claims are limited to detection of the recited mRNA in breast cancer samples, while the dataset of the instant claims are any sample from any ER+ breast cancer patient. Thus the amendment appears to introduce new matter.
Claims 21-33 were added by amendment on 3/9/2022. The response merely alleges support for the amendment can be found throughout the specification as originally filed.
Independent claim 21 requires, “treating the subject with an adjuvant therapy selected from an aromatase inhibitor, anti-mTOR therapy, anti-HER2 therapy, and endocrine therapy; wherein (a) if the subject has a high risk of recurrence, the subject is treated with the adjuvant therapy for more than 5 years after the initial treatment, or (b) if the subject has a low risk of recurrence, the subject is treated with the adjuvant therapy for 5 years or less after the initial treatment.”
Independent claim 32 requires, “either (a) treating the high-risk subject with a second therapy comprising an aromatase inhibitor or anti-mTOR therapy or anti-HER2 therapy or endocrine therapy, wherein the first therapy and second therapy are different, or (b) ceasing the first therapy after 5 years in the low-risk subject.”
Response to Arguments
The response begins traversing the rejection asserting, “The Office alleges that Applicants' cited portions of the disclosure "do not provide any indication disclosure views the initial investigation as cancer patients as part of the invention." Id. at 4. As the entirety of the disclosure is directed toward breast cancer patients, Applicants are unclear on the Office's rationale that such an indication or patient population is unsupported. For at least this reason, Applicants disagree with the rejection and request it be withdrawn.” This argument has been thoroughly reviewed is not considered persuasive as the originally filed claims failed to provide any support for step (a). Further the specification recites data set 10 times and only teaches ER+ dataset with a 5 year retrospective study (page 3 and page 10). This does not provide the basis for calculating BCI from any sample from any sample of any subject with ER+ breast cancer.
The response continues by asserting, “The Office also alleges that "the specification and initially filed claims are limited to detection of the recited mRNA in breast cancer samples, while the dataset of the instant claims are any sample from any ER+ breast cancer patient." Applicants disagree with the Office's construction of the claims, which clearly recite a sample "comprising ER+ breast cancer cells." For at least this reason, Applicants request withdrawal of this rejection..” This argument has been thoroughly reviewed but is not considered persuasive as step (a) is not limited to a sample "comprising ER+ breast cancer cells:
(a) calculating or having calculated a breast cancer index (BCI) for a dataset of human subjects having estrogen receptor positive (ER+) breast cancer, comprising:
(i) measuring or having measured mRNA expression levels of the genes homeobox B13 (HoxB13), interleukin 17 receptor B (IL17BR), budding uninhibited by benzimidazoles 1 beta (Bub1B), centromere protein A, isoform a (CENPA), never in mitosis gene a-related kinase 2 (NEK2), Rac GTPase activating protein 1 (RACGAP1), and ribonucleotide reductase M2 (RRM2) of the dataset subjects;
(ii) determining or having determined the ratio of expression levels of HoxB13/IL17BR (H:I);
(iii) calculating or having calculated a molecular grade index (MGI),comprising summing the expression levels of Bub1B, CENPA, NEK2,RACGAP1, and RRM2 using coefficients determined from principal component analysis of the dataset; and
(iv) linearly combining or having linearly combined the H:I and the MGI as continuous variables;
The response continues by arguing, “the Office also maintains a rejection against the treating language of the independent claims, contending that "the cited portions of the specification appear to be limited to an additional 5 year treatment, but not the new range of 5 years or more." Office Action at 5-6. With respect, the Office has perhaps overlooked the part of Applicants' prior response citing to literal support for the language at issue. Applicants, therefore, reiterate that the specification discloses that an extended therapy, such as adjuvant therapy, "may be applied during a subsequent period for up to five years or more" (page 22, emphasis added) or "for a period of five years or more after the initial treatment period." (page 24, emphasis added). The Office's statements concern language from page 21, which Applicants did not rely upon in the last reply. Applicants respectfully request the Office to carefully consider the arguments presented in responses and to withdraw this rejection. “ This argument has been thoroughly reviewed but is not considered persuasive as the cited portions are limited to aromatase inhibitor, targeted therapy, endocrine therapy, which does not specifically teach anti-mTor or anti-Her2 therapy and thus do not support the full breadth of the claims.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 21, 22-27, 29-30, 32-33 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 21 has been amended to recite, “(i) measuring or having measured mRNA expression levels of the genes homeobox B13 (HoxB13), interleukin 17 receptor B (IL17BR), budding uninhibited by benzimidazoles 1 beta (Bub1B), centromere protein A, isoform a (CENPA), never in mitosis gene a-related kinase 2 (NEK2), Rac GTPase activating protein 1 (RACGAP1), and ribonucleotide reductase M2 (RRM2) of the dataset subjects;(ii) determining or having determined the ratio of expression levels of HoxB13IL17BR (H:I ).” The metes and bounds are unclear if the determining the ratio is for each subject or a combination of all subjects.
Claim 21 further recites, “(iii) calculating or having calculated a molecular grade index (MGI),comprising summing the expression levels of Bub1B, CENPA, NEK2,RACGAP1, and RRM2 using coefficients determined from principal component analysis of the dataset;.” The metes and bounds are unclear what coefficients are being determined, how coefficients are being used, how the statical method of principle component analysis is being performed. Thus it is unclear how summing is done. Additionally it is unclear if the calculating or having calculated is for each subject or all the subjects of the data set combined.
Claim 21 continues by reciting, “(iv) linearly combining or having linearly combined the H:I and the MGI as continuous variables.” This is vague, unclear and incomplete as to how combining is done and how continuous variables limits the claim.
The claim continues by recites, “(b) selecting or having selected a BCI cutoff, wherein the BCI cutoff is or has been selected such that the risk of cancer recurrence is less than 5% for a BCI below the BCI cutoff.” This is confusing and unclear as BCI as calculated does not require risk of cancer recurrence. It is unclear further as the claim does not require the subjects had distant recurrence and human dataset subjects had been diagnosed long enough to have recurrence.
While steps a) and c) of the instant claims provide calculating of BCI and provide some guidance on how to calculate BCI. The claims are confusing and unclear as the art of Sgroi et al (WO2012/079059 A2, published June 14, 2012), Jerevall (Homeobox B13 in breast cancer – Prediction of tamoxifen benefit) (2011) also teach BCI. Thus it is unclear what is required of the recitation of BCI.
Claim 21 continues by reciting, “(iii) calculating or having calculated an MGI of the subject, comprising summing the expression levels of Bub1B, CENPA, NEK2, RACGAP1, andRRM2, using coefficients determined from principal component analysis of the dataset.” The metes and bounds are unclear as the metes and bounds of how coefficients are determined by principle component analysis as detailed previously.
Claim 23 recites, “wherein more than 50% of the dataset subjects is more than 50% of the dataset subjects BCI below the BCI cutoff.” The metes and bounds are unclear how this limits the active steps of the claim as this appears to be a possible outcome of the analysis, but not an active step. Further it is confusing as it is unclear how BCI is calculated for the dataset and how the cutoff is determined.
Claim 24 recites, “wherein more than 55% of the dataset subjects is more than 50% of the dataset subjects BCI below the BCI cutoff.” The metes and bounds are unclear how this limits the active steps of the claim as this appears to be a possible outcome of the analysis, but not an active step. Further it is confusing as it is unclear how BCI is calculated for the dataset and how the cutoff is determined.
Claim 26 recites, “wherein more than 60% of the dataset subjects is more than 50% of the dataset subjects BCI below the BCI cutoff.” The metes and bounds are unclear how this limits the active steps of the claim as this appears to be a possible outcome of the analysis, but not an active step. Further it is confusing as it is unclear how BCI is calculated for the dataset and how the cutoff is determined.
Claim 32 has been amended to recite, “(i) measuring or having measured mRNA expression levels of the genes homeobox B13 (HoxB13), interleukin 17 receptor B (IL17BR), budding uninhibited by benzimidazoles 1 beta (Bub1B), centromere protein A, isoform a (CENPA), never in mitosis gene a-related kinase 2 (NEK2), Rac GTPase activating protein 1 (RACGAP1), and ribonucleotide reductase M2 (RRM2) of the dataset subjects;(ii) determining or having determined the ratio of expression levels of HoxB13IL17BR (H:I ).” The metes and bounds are unclear if the determining the ratio is for each subject or a combination of all subjects.
Claim32 further recites, “(iii) calculating or having calculated a molecular grade index (MGI),comprising summing the expression levels of Bub1B, CENPA, NEK2,RACGAP1, and RRM2 using coefficients determined from principal component analysis of the dataset;.” The metes and bounds are unclear what coefficients are being determined, how coefficients are being used, how the statical method of principle component analysis is being performed. Thus it is unclear how summing is done. Additionally it is unclear if the calculating or having calculated is for each subject or all the subjects of the data set combined.
Claim 32 continues by reciting, “(iv) linearly combining or having linearly combined the H:I and the MGI as continuous variables.” This is vague, unclear and incomplete as to how combining is done and how continuous variables limits the claim.
The claim continues by recites, “(b) selecting or having selected a BCI cutoff, wherein the BCI cutoff is or has been selected such that the risk of cancer recurrence is less than 5% for a BCI below the BCI cutoff.” This is confusing and unclear as BCI as calculated does not require risk of cancer recurrence. It is unclear further as the claim does not require the subjects had distant recurrence and human dataset subjects had been diagnosed long enough to have recurrence.
While steps a) and c) of the instant claims provide calculating of BCI and provide some guidance on how to calculate BCI. The claims is confusing and unclear as the Art of Sgroi et al (WO2012/079059 A2, published June 14, 2012), Jerevall (Homeobox B13 in breast cancer – Prediction of tamoxifen benefit) (2011) also teach BCI. Thus it is unclear what is required of the recitation of BCI.
Claim 32 continues by reciting, “(iii) calculating or having calculated an MGI of the subject, comprising summing the expression levels of Bub1B, CENPA, NEK2, RACGAP1, andRRM2, using coefficients determined from principal component analysis of the dataset.” The metes and bounds are unclear as the metes and bounds of how coefficients are determined by principle component analysis as detailed previously.
Response to Arguments
The response begins traversing the rejections asserting, “The Office alleges that it is unclear if MGI, H:I, and BCI are determined for individual subjects in the dataset or a combination of all subjects in the dataset. Id. at 6- 9. In view of guidance in the specification (e.g., paragraph [0061] and the Examples), as well as claim language reciting that certain specified percentages of dataset subjects have a BCI value below the BCI cut-off, Applicants assert that it is clear that these indices are calculated for individual subjects.” The reference to (0061} is a little confusing as the specification as originally filed provides no paragraph numbers. While PGPUB of the specification teaches, “[0061] Where BCI is used, the BCI may be calculated in any manner known in the art. In some embodiments, BCI is calculated by assessing the individual risk of cancer recurrence as part of a continuous BCI variable, wherein the risk of recurrence increases in a linear relationship with the BCI variable.” This argument has been thoroughly reviewed but is not considered persuasive as merely indicates it can be calculated by any means, but does not define how it is calculated.
The response continues by arguing, “The Office also alleges that the recited coefficients and use of principal component analysis (PCA) in the "summing" of subparagraphs (iii) are unclear and similarly alleges that the "combining" of subparagraphs (iv) is unclear. Id. at 6-10. However, Applicants assert that, given the guidance provided in the Examples and the general knowledge available to bioinformaticians/biostatisticians, that a person having ordinary skill in the art could readily practice the invention (including but not limited to determining coefficients using PCA), based on the dataset data collected for a given group of subjects, and know how to practice the claims.” This is arguments of counsel. MPEP 716.01(c) makes clear that "The arguments of counsel cannot take the place of evidence in the record. In re Schulze , 346 F.2d 600, 602, 145 USPQ 716, 718 (CCPA 1965). Here, the statements regarding the general knowledge available to bioinformaticians/biostatisticians, that a person having ordinary skill in the art could readily practice the invention.
This should not be construed as an invitation for providing evidence. As further stated in the MPEP 716.01 regarding the timely submission of evidence:
A) Timeliness.
Evidence traversing rejections must be timely or seasonably filed to be entered and entitled to consideration. In re Rothermel, 276 F.2d 393, 125 USPQ 328 (CCPA 1960). Affidavits and declarations submitted under 37 CFR 1.132 and other evidence traversing rejections are considered timely if submitted:
(1) prior to a final rejection,
(2) before appeal in an application not having a final rejection, or
(3) after final rejection and submitted
(i) with a first reply after final rejection for the purpose of overcoming a new ground of rejection or requirement made in the final rejection, or
(ii) with a satisfactory showing under 37 CFR 1.116(b) or 37
CFR 1.195, or
(iii) under 37 CFR 1.129(a).
The response continues by asserting, “The Office contends that part (b) of claim 21 and claim 32 "is confusing and unclear as BCI as calculated does not require risk of cancer recurrence. It is unclear further as the claim does not require the subjects had distant recurrence and human dataset subjects had been diagnosed long enough to have recurrence." Id. at 7, 9. Applicants disagree, noting that a reasonable construction of the claim language clearly indicates that some portion of the dataset subjects had recurrence, such that the claimed method uses BCI to indicate whether a subject is at high or low risk of cancer recurrence (e.g., claim 21), including distant recurrence (e.g., claim 27). The Office also appears to compare the claimed use of BCI to its alleged use in other publications, see id., but it is unclear to Applicants how further uses of BCI, outside the scope of the present application, are relevant to the definiteness of the present claims.” This argument has been thoroughly reviewed but is not considered persuasive as the claims recite:
(a) calculating or having calculated a breast cancer index (BCI) for a dataset of human subjects having estrogen receptor positive (ER+) breast cancer, comprising:
(i) measuring or having measured mRNA expression levels of the genes homeobox B13 (HoxB13), interleukin 17 receptor B (IL17BR), budding uninhibited by benzimidazoles 1 beta (Bub1B), centromere protein A, isoform a (CENPA), never in mitosis gene a-related kinase 2 (NEK2), Rac GTPase activating protein 1 (RACGAP1), and ribonucleotide reductase M2 (RRM2) of the dataset subjects;
(ii) determining or having determined the ratio of expression levels of HoxB13/IL17BR (H:I);
(iii) calculating or having calculated a molecular grade index (MGI),comprising summing the expression levels of Bub1B, CENPA, NEK2,RACGAP1, and RRM2 using coefficients determined from principal component analysis of the dataset; and
(iv) linearly combining or having linearly combined the H:I and the MGI as continuous variables;
Thus the claims has no explicit requirement of recurrence for the dataset. Further the recitation of “has been selected such that the risk of cancer recurrence is less than 5% for a BCI below the BCI cutoff.” Thus a recurrence of less than 5% encompasses no recurrence. Thus this argument is not persuasive. With respect to the teachings of the art with respect to terms of BCI, MGI, etc. result in confusion as the cited prior art provides additional means of calculating and the instant claims are vague, unclear and incomplete as to how to calculate. Thus it adds to the confusion of how the calculations are performed.
The response traverses the rejection with respect to claims 24-26 asserting, “These recited features are not "a possible outcome of the analysis" but rather further characterization of the dataset subjects and the determination of the BCI cutoff.” This argument has been thoroughly reviewed but is not considered persuasive as this is an outcome of the analysis and determined by the dataset, and not an active step of the claims. The arguments the limitations somehow limit the calculations is arguments of counsel. MPEP 716.01(c) makes clear that "The arguments of counsel cannot take the place of evidence in the record. In re Schulze , 346 F.2d 600, 602, 145 USPQ 716, 718 (CCPA 1965). Here, the statements asserting they limit the data set are arguments of counsel. Further it is unclear if applicant actually had datasets which provide for this outcome.
This should not be construed as an invitation for providing evidence. As further stated in the MPEP 716.01 regarding the timely submission of evidence:
A) Timeliness.
Evidence traversing rejections must be timely or seasonably filed to be entered and entitled to consideration. In re Rothermel, 276 F.2d 393, 125 USPQ 328 (CCPA 1960). Affidavits and declarations submitted under 37 CFR 1.132 and other evidence traversing rejections are considered timely if submitted:
(1) prior to a final rejection,
(2) before appeal in an application not having a final rejection, or
(3) after final rejection and submitted
(i) with a first reply after final rejection for the purpose of overcoming a new ground of rejection or requirement made in the final rejection, or
(ii) with a satisfactory showing under 37 CFR 1.116(b) or 37
CFR 1.195, or
(iii) under 37 CFR 1.129(a).
Thus the rejections are maintained.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 21, 22-27, 29-30, 32-33 is/are rejected under 35 U.S.C. 103 as being unpatentable over Sgroi et al (WO2012/079059 A2, published June 14, 2012), Jerevall (Homeobox B13 in breast cancer – Prediction of tamoxifen benefit) (2011) , Sgroi (Journal of clinical oncology (2011) Prediction of late recurrences by breast cancer index in the NCIC CTG MA.17 cohort, Ma (Clinical Cancer Research (2008) volume 14, pages 2601-2608 and supplemental) Jankowitz (. Breast Cancer Research 2011, 13:R98) and Ma(BRIEFINGS IN BIOINFORMATICS. VOL 12. NO 6. 714 -722 doi:10.1093/bib/bbq090 Advance Access published on 17 January 2011.)
Ma(BRIEFINGS IN BIOINFORMATICS. VOL 12. NO 6. 714 -722 doi:10.1093/bib/bbq090 Advance Access published on 17 January 2011.) is being referred to as Ma (PCA).
Ma (Clinical Cancer Research (2008) volume 14, pages 2601-2608 and supplemental) is being referred to as Ma (BCI)
The art of Sgroi, Jerevall, Ma(BCI) demonstrate expression of all of HOXB13, IL17BR, BUB1B, CENPA, NEK2, RACGAP1, and RRM2were known and implicated in ER+ node negative breast cancer diagnosis/ prognosis. The art Sgroi, Jerevall, Ma(BCI) specifically teaches determining a ratio of H:I and MGI from a populations of subjects breast cancer including ER+. The art of Sgroi claims the combining of H:I and MGI to produce a BCI and use in prognoses of aromatase inhibitor and endocrine therapy in breast cancer. Further Sgroi, Jerevall, Ma teaches determining threshold levels and treatments based thereon H:I, BCI and MGI.
The recitation of linearly combining or having linearly combined the H:I and the MGI as continuous variables” is broad and encompass any linear combination of the values, based on the declaration by Bao , Lesson 7.3 solving linear systems by linear combination (April 9, 2013, pages 1-8) solving linear systems by linear combination demonstrates the preferred definition of applicant and Dr Bao is not limiting in the field of algebra. Finally linear combination (April 10, 2010, pages 1-2) teaches in 5.1 subtracting 3v1 from v2 is a linear combination. Study.com (https://study.com/academy/lesson/linear-combination-definition-examples.html, 3/2/2020), MathBoot Camps (https://www.mathbootcamps.com/linear-combinations-vectors/, 3/4/2020) this encompasses addition.
With regards to claim 21 and 32 Sgroi teaches, “The disclosure relates to the identification and use of gene expression profiles, or patterns, with clinical relevance to breast cancer. In particular, the disclosure is based in part on the identities of genes that are expressed in correlation with the likelihood of cancer recurrence after initial treatment with an aromatase inhibitor or other endocrine therapy. The levels of gene expression form a molecular index that is able to predict clinical outcome, and so prognosis, for a patient after initial treatment with an aromatase inhibitor or other endocrine therapy.” Sgori teaches, “classifying the subject as expected to benefit from treatment with a different second endocrine therapy after cessation of the first endocrine therapy, wherein said classifying is based upon an elevated expression level of HoxB13.” Sgori teaches, “The disclosure also includes detecting gene expression where high HoxB13 expression is an indicator of increased likelihood of cancer recurrence in the subject following an initial endocrine therapy, such as adjuvant tamoxifen therapy. The methods may thus include identifying the subject as likely, or unlikely, to experience local cancer recurrence, and further include switching treatment modalities for the subject to address the expected outcome. As a non-limiting example, determination of a likelihood of recurrence in the absence of an extended, post-initial treatment, therapy may be used to confirm the suitability of, or to select, an extended therapy with a switch in the anti-estrogen and/or anti-aromatase modality used.” Thus Sgori teaches continuing or changing therapy based on HI.
Sgroi teaches, “Goss et al. (J. Clin. Oncol. , 26(12): 1948-1955, 2008) report results from a trial examining the use of letrozole started within 3 months after five years of adjuvant tamoxifen in subjects with primary ER+ breast cancer. The results suggested that post-tamoxifen treatment with letrozole improves breast cancer-free survival and distant breast cancer-free survival. But Goss et al. provided no means by which to predict which subjects, treated for five years with tamoxifen, would benefit from subsequent letrozole treatment. Therefore, there was no means to direct letrozole treatment only to the subjects for whom a benefit is expected. So letrozole treatment was applied to subjects for whom no benefit would have been expected, resulting in an overtreatment of the population of breast cancer-free subjects treated with for five years with tamoxifen.” (page 2)
Sgroi teaches, “The disclosure is based in part on the discovery and determination of gene expression levels in breast cancer tumor cells that are correlated with a beneficial switch in anti-breast cancer chemotherapy. In some cases, the switch is from one form of endocrine therapy to another. The expression levels may be used to provide prognostic information, such as cancer recurrence, and predictive information, such as responsiveness to certain therapies. In a first aspect, the disclosure includes a method to identify, or classify, a population of subjects initially treated with an anti-estrogen or anti-aromatase therapy into at least two subpopulations. A first subpopulation would be expected to benefit from a switch in therapy, such as a switch to another anti-estrogen or anti-aromatase therapy. A second subpopulation would not be expected to benefit. In some cases, the initial therapy is with tamoxifen, such as adjuvant tamoxifen therapy for a period of about five years or less. Optionally, the switch is to letrozole, or other anti-aromatase, therapy. The disclosure includes means for a population of subjects treated in this manner, and breast cancer-free during treatment, to be classified into the first, and/or the second, subpopulations. ”
Sgroi claims, “determining the expression levels of the seven genes in the disclosed Breast Cancer Index (BCI) from said cDNA, wherein said genes are HoxBJ3, ILl7BR, BublB, CENPA, NEK2, RACGAPI, and RRM2, to determine a BCI value.”(claim 2). Sgroi teaches
Sgroi teaches, “A continuous risk model was built by combining H:I and MGI as continuous variables” (page 25). Sgroi teaches, “The use of all seven disclosed genes is referred to as the Breast Cancer Index (BCI).”
Sgroi teaches, “In additional aspects, HoxB13 expression, and/or the BCI, may be used to predict late recurrence of cancer in a breast cancer patient. Non-limiting examples of late recurrence include after 5 years of treatment with tamoxifen, but also includes after 4 years, after 3 years, or after 2 years or less time of treatment with tamoxifen. Similarly, HoxB13 expression, and/or the BCI, may be used to predict responsiveness to letrozole or other anti-estrogen or anti-aromatase therapy after the above time periods to inhibit late recurrence.”
Sgori teaches, " Generally, and with respect to MGI, it is preferred that the expression levels of the disclosed genes are combined to form a single index that serves as a strong prognostic factor and predictor of clinical outcome(s). The index is a summation of the expression levels of the genes used and uses coefficients determined from principle component analysis to combine cases of more than one disclosed gene into a single index. The coefficients are determined by factors such as the standard deviation of each gene's expression levels across a representative dataset, and the expression value for each gene in each sample. The representative dataset is quality controlled based upon the average expression values for reference gene(s) as disclosed herein.” (page 24).
Sgori teaches, “In cases using HoxB13 expression alone or the HoxB13:IL17BR (H:I) ratio, a cutoff value may be used to define breast cancer cells as having either a "high" and a "low" value corresponding to the expression. In some embodiments, a cutoff may be used to define breast cancer cells as having either a "high H/I" and a "low H/I" value. As a non-limiting example, the value of 0.06 may be used in the manner of Ma et al. In other embodiments, the cutoff may be the average expression of HoxB 13 in breast cancer cells from afflicted subjects. In additional possible embodiments, the cutoff may be the average value of H/I in breast cancer cells from afflicted subjects as determined by the average HoxB 13 expression/the average IL17BR expression.”(page 14 )(claim 44)
Sgori teaches, “So using a threshold, or cutoff, of 0 (zero) as a non-limiting example for MGI with all five genes, the disclosed methods provide two possible assay outcomes for a given sample: "high risk MGI" corresponding to a value above 0 (zero) and "low risk MGI" corresponding to a value < 0. A "high risk MGI" is indicative of a "high risk" cancer, including breast cancer that is analogous to that of a Grade III tumor as defined by methodologies and standards known in the field. A "low risk MGI" is indicative of a "low risk" cancer, including breast cancer, that is analogous to that of a Grade I tumor as defined by methodologies and standards known in the field.” Sgori teaches, “A continuous risk model was built by combining H:I and MGI as continuous variables. The linearity of these two variables were checked by fitting a Cox proportional hazard regression model with restricted cubic splines, and H:I demonstrated significant non-linearity. A polynomial function of H:I was used to approximate the restricted models using Akaike Information Criterion. The resulting predictor from the final Cox regression model was then re-scaled into the range of 0 to 10, which is referred to as the BCI.”(page 25)
Sgori teaches data with respect to the disclosed genes was determined from a dataset of subjects (example 1).
Sogri (abs) teaches, ” Patient characteristics for the case-control study were similar to that from the overall study. Characteristics for cases (N=83) and controls (N=166) were not significantly different except for treatment. A higher percentage of controls compared to cases tended to be categorized as low risk by BCI (58% vs 43%), while a lower percentage of controls than cases tended to be categorized as high risk by BCI (34% vs 24%). In univariate analysis, treatment, BCI, H:I and HOXB13, but not tumor grade or MGI, were significant predictors of late recurrence. After adjusting for standard variables (age, tumor grade and treatment), BCI (OR 2.37; P=0.03), H:I (OR 2.55; P=0.04) and HOXB13 (OR 1.35; P=0.02) remained significant predictors of recurrence. HOXB13 expression at diagnosis predicted patient benefit from extended endocrine therapy with letrozole.”
Sgroi (abs) teaches, “ A higher percentage of controls compared to cases tended to be categorized as low risk by BCI (58% vs 43%), while a lower percentage of controls than cases tended to be categorized as high risk by BCI (34% vs 24%)>
Jankowitz teaches, “we report the prognostic performance of the gene expression-based BCI within a clinical case series of patients with ER+ LN- breast cancer and demonstrate that BCI is a highly significant predictor of distant metastasis and death in patients treated with adjuvant tamoxifen, with or without chemotherapy. With categorical stratification, BCI identified more than 50% of the patients with low risk with a 10-year rate of recurrence of 6.6% and breast cancer-specific mortality rate of 3.8%. In a multivariate model that includes clinicopathological covariates, BCI remained a significant factor associated with recurrence risk and mortality.” Jankowitz teaches study population, BCI calculation. (pages 2-3)
Jerevall teaches, “We brought the combined index of HOXB13:IL17BR+MGI a step further and developed a continuous risk index to allow for individual risk assessment of the recurrence risk. In order to maximize the accuracy, the algorithm was trained to retain the entirety of the prognostic information available using the ER-positive tamoxifen-treated cohort. The algorithm, called Breast Cancer Index (BCI), assigns each patient an individual risk score between zero and ten, corresponding to a certain level of risk of distant recurrence.” (page 41)
Jerevall teaches, “Ma and colleagues (2008) demonstrated that the combined index of binary HOXB13:IL17BR and MGI were complementary prognostic factors outperforming either alone in predicting risk of recurrence in breast cancer patients. Using this combinatorial approach, a risk classification of distant metastasis could be made, stratifying patients into three risk groups. Our study, which is described in Paper II, was performed in collaboration with employees of bioTheranostics, Inc. (former
Aviara Dx, Inc. and Arcturus Bioscience, Inc.) and the Molecular Pathology Research Unit at Massachusetts General Hospital. These are named inventors on a patent to use the HOXB13:IL17BR ratio for breast cancer prognosis. Herein, we utilized a cohort of 808 patients from the randomized Stockholm trial for validation of the prognostic utility of the combined index. RNA was extracted from FFPE tissue, and the subsequent gene expression analysis was successfully for a total of 769 cases, of which 588 were ER-positive and included in the validation analysis.” (page 41)
Jerevall teaches, “The initial analysis in the training of BCI, almost 60% of the tamoxifen-treated patients were estimated to have a rate of distant recurrence of 1.7% (95% CI: 0-3.5) and a death rate of 1.1% (95% CI: 0-2.6)” (page 41-42)
Jerevall teaches, “The continuous risk index, BCI, which is a further development of HOXB13:IL17BR and MGI, identifies a major proportion of lymph node negative patients with a very low risk of distant recurrence. It has also significant prognostic value and may therefore help clinicians to make better informed treatment decisions in order to spare toxic chemotherapy for a large group of breast cancer patients.” (page 49).
Sgroi teaches the use of data from patients to determine the cutoff (example 1).
Sgrio and Jerevall do not specifically teach treating subjects or stopping treatment based on BCI levels, or use of only high risk of recurrence or low risk of recurrence. Sgrio and Jerevall do not teach use of PCA to find coefficients.
However, Sgroi teaches, “So the disclosure includes a method to identify a patient, from a population of patients with ER+ breast cancer cells treated with a first endocrine therapy and cancer-free for a period of time, as belonging to a subpopulation of patients with a better prognosis if treated with an alternative endocrine therapy. In some cases, the breast cancer in the subject is node negative. The disclosure provides a non-subjective means for the identification of patients in the subpopulation.” Sgroi teaches, “In cases using HoxB13 expression alone or the HoxB13:IL17BR (H:I) ratio, a cutoff value may be used to define breast cancer cells as having either a "high" and a "low" value corresponding to the expression. In some embodiments, a cutoff may be used to define breast cancer cells as having either a "high H/I" and a "low H/I" value. As a non-limiting example, the value of 0.06 may be used in the manner of Ma et al. In other embodiments, the cutoff may be the average expression of HoxB 13 in breast cancer cells from afflicted subjects. In additional possible embodiments, the cutoff may be the average value of H/I in breast cancer cells from afflicted subjects as determined by the average HoxB 13 expression/the average IL17BR expression.”
Sgori teaches compare BCI high vs BCI low + intermediate (table 5).
Sgroi teaches, “So using a threshold, or cutoff, of 0 (zero) as a non-limiting example for MGI with all five genes, the disclosed methods provide two possible assay outcomes for a given sample: "high risk MGI" corresponding to a value above 0 (zero) and "low risk MGI" corresponding to a value < 0. A "high risk MGI" is indicative of a "high risk" cancer, including breast cancer that is analogous to that of a Grade III tumor as defined by methodologies and standards known in the field. A "low risk MGI" is indicative of a "low risk" cancer, including breast cancer, that is analogous to that of a Grade I tumor as defined by methodologies and standards known in the field.”
Sgroi teaches, “classifying the subject as expected to benefit from treatment with a different second endocrine therapy after cessation of the first endocrine therapy, wherein said classifying is based upon an elevated expression level of HoxB13.”
Therefore it would have been prima facie obvious to one of ordinary skill in the prior to the effective filing date of the claims to use a sum or linear combination MGI and H:I to determine a BCI in a group of breast cancer patients and test subjects and identify subject with low risk of cancer recurrence and cessation of treatment after 5 years. The artisan would be motivated as Sgroi, Sgori (abs), Jervall suggest BCI or combinations of MGI and H:I can be used to determine hi and low risk of recurrence and therapies. The artisan would have a reasonable expectation of success as the artisan is merely using known method to obtain and analyze a sample to direct treatment as taught by Sgroi and Jerevall.
In re Kerkhoven, 626 F.2d 846, 850, 205 USPQ 1069, 1072 (CCPA 1980) (citations omitted) sates, “It is prima facie obvious to combine two compositions each of which is taught by the prior art to be useful for the same purpose, in order to form a third composition to be used for the very same purpose.... [T]he idea of combining them flows logically from their having been individually taught in the prior art.” In the instant case the combination (addition) of two known prognosis index (H:I and MGI) to provide a composite index (BCI) is obvious.
However, Ma(BCI) teaches, “The combination of MGI and HOXB13:IL17BR outperforms either alone and identifies a subgroup (30%) of early stage estrogen receptor ^ positive breast cancer patients with very poor outcome despite endocrine therapy” (abstract). Ma(BCI) teaches, “MGI+HOXB13:IL17BR” in supplemental figure 7.
Ma (PCA) teaches, “Without loss of generality, we use genomic study with gene expression measurements as a representative example but note that analysis techniques discussed in this article are also applicable to other types of bioinformatics studies. Principal component analysis (PCA) is a classic dimension reduction approach. It constructs linear combinations of gene expressions, called principal components (PCs). The PCs are orthogonal to each other, can effectively explain variation of gene expressions, and may have a much lower dimensionality. PCA is computationally simple and can be realized using many existing software packages.” (abstract). Ma (PC) teaches, “PCA is one of the oldest dimension reduction approaches [3, 4]. It searches for linear combinations of the original measurements called principal components (PCs) that can effectively represent effects of the original measurements. PCs are orthogonal to each other and may have dimensionality much lower than that of the original measurements. Because of its computational simplicity and satisfactory statistical properties, PCA has been extensively used in multiple statistical areas. Most recently, it has been used in bioinformatics studies, particularly gene expression studies, to reduce the dimensionality of high-throughput measurements” (page 715, 1st column, 2nd paragraph). Ma (PCA) teaches, “For example, in cancer prognosis studies , less than 10 PCs can be sufficient to represent pathways composed of hundreds of genes.(page 717, 1st paragraph).
Therefore it would have been prima facie obvious to one of ordinary skill in the prior to the effective filing date of the claims to use a linear combination by adding MGI using coefficients determine by PCA and H:I to determine a BCI and identify subjects with high risk of cancer recurrence and switching from tamoxifen after 5 years of letrozoleand low risk of recurrence. The artisan would be motivated as Sgroi suggest BCI or combinations of MGI and H:I can be used to determine prognosis and therapies and specifically teaches switching from tamoxifen to letrozole. Further the artisan would be motivated as Ma explicitly states in supplementary figure 7 to add MGI and H:I. The artisan would be motivated to use PCA as Ma(PCA) teaches, “For example, in cancer prognosis studies , less than 10 PCs can be sufficient to represent pathways composed of hundreds of genes.(page 717, 1st paragraph). The artisan would have a reasonable expectation of success as the artisan is merely using known method to obtain and analyze a sample to direct treatment as taught by Sgroi.
Claims 23-26 merely set forth the wherein clauses and the intended outcome of the claims and thus are not limitations relating to positive active steps of the claims.
Claim 23 to 25 are unclear how they relate to the independent claim which appears to provide another method of selecting BCI cutoff.
With regards to claim 26 Sgroi teaches, “In additional aspects, HoxB13 expression, and/or the BCI, may be used to predict late recurrence of cancer in a breast cancer patient. Non-limiting examples of late recurrence include after 5 years of treatment with tamoxifen, but also includes after 4 years, after 3 years, or after 2 years or less time of treatment with tamoxifen. Similarly, HoxB13 expression, and/or the BCI, may be used to predict responsiveness to letrozole or other anti-estrogen or anti-aromatase therapy after the above time periods to inhibit late recurrence.”
Sgrio teaches, “The disclosure is based in part on the discovery and determination of gene expression levels in breast cancer tumor cells that are correlated with a beneficial switch in anti-breast cancer chemotherapy.”(page 2, middle)
With regards to claims 26, 33, Sgroi teaches, “In additional aspects, HoxB13 expression, and/or the BCI, may be used to predict late recurrence of cancer in a breast cancer patient. Non-limiting examples of late recurrence include after 5 years of treatment with tamoxifen, but also includes after 4 years, after 3 years, or after 2 years or less time of treatment with tamoxifen. Similarly, HoxB13 expression, and/or the BCI, may be used to predict responsiveness to letrozole or other anti-estrogen or anti-aromatase therapy after the above time periods to inhibit late recurrence.”
Sgroi teaches, “Goss et al. (J. Clin. Oncol. , 26(12): 1948-1955, 2008) report results from a trial examining the use of letrozole started within 3 months after five years of adjuvant tamoxifen in subjects with primary ER+ breast cancer. The results suggested that post-tamoxifen treatment with letrozole improves breast cancer-free survival and distant breast cancer-free survival. (page 2, top).”
Response to Arguments
The response traverses the rejection asserting none of the prior art specifically teaches only high risk of recurrence and low risk of recurrence without an intermediate risk. This argument has been thoroughly reviewed but is not considered persuasive as Sgori teaches compare BCI high vs BCI low + intermediate (table 5). Further, Sgroi teaches, “So using a threshold, or cutoff, of 0 (zero) as a non-limiting example for MGI with all five genes, the disclosed methods provide two possible assay outcomes for a given sample: "high risk MGI" corresponding to a value above 0 (zero) and "low risk MGI" corresponding to a value < 0. A "high risk MGI" is indicative of a "high risk" cancer, including breast cancer that is analogous to that of a Grade III tumor as defined by methodologies and standards known in the field. A "low risk MGI" is indicative of a "low risk" cancer, including breast cancer, that is analogous to that of a Grade I tumor as defined by methodologies and standards known in the field.” Thus Sgroi teaches stratifying subjects into two groups.
The response asserts the teachings of Sgori (wo ) are limited to two groups with respect to BCI. This argument has been thoroughly reviewed but is not considered persuasive as table 5 teaches
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Further Sgroi (abs) teaches, “ A higher percentage of controls compared to cases tended to be categorized as low risk by BCI (58% vs 43%), while a lower percentage of controls than cases tended to be categorized as high risk by BCI (34% vs 24%).
The response continues by asserting, “as the Office notes (Office Action at 24), Sgroi contemplates a two- category scheme using MGI (see Sgroi at p. 17 line 29 - p. 18 line 3), it does not do so or BCI as claimed, which accounts for additional parameters and applies a different cutoff compared to MGI. Further, Sgroi PCT's combination of the separate intermediate and low groups in Table 5 is not the same as the claimed method, which eliminates the intermediate group.” This argument has been thoroughly reviewed but is not considered persuasive as Table 5 BCI high vs intermediate+ low is two groups for BCI. Further it is unclear what additional parameters the response is alleging. This argument is vague and unclear what is being asserted.
The response traverses the rejection by asserting the specification on page 2 and 13 demonstrate the instant invention provides for a significant advance. This argument has been thoroughly reviewed but is not considered persuasive as the response is arguing the teachings of the specification and has not specifically indicated which claim limitations are not taught or rendered obvious by the prior art. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., page 2 and 13 are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim 21, 22-27, 29-30, 32-33 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1-20 of copending Application No. 17/386380 in view of Ma(BRIEFINGS IN BIOINFORMATICS. VOL 12. NO 6. 714 -722 doi:10.1093/bib/bbq090 Advance Access published on 17 January 2011.) is being referred to as Ma (PCA).. Although the claims at issue are not identical, they are not patentably distinct from each other because they are coextensive in scope.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
The instant claims are drawn to A method of treating a human subject who has been diagnosed with breast cancer and is receiving or has received an initial treatment, the method comprising the steps of: (a) calculating or having calculated a breast cancer index (BCI) for a dataset of human subjects having estrogen receptor positive (ER+) breast cancer, comprising:(i) measuring or having measured mRNA expression levels of the genes homeobox B13 (HoxB13), interleukin 17 receptor B (IL17BR), budding uninhibited by benzimidazoles 1 beta (Bub1B), centromere protein A, isoform a (CENPA), never in mitosis gene a-related kinase 2 (NEK2), Rac GTPase activating protein 1 (RACGAP1), and ribonucleotide reductase M2 (RRM2) of the dataset subjects;(ii) determining or having determined the ratio of expression levels of HoxB13IL17BR (H:I );(iii) calculating or having calculated a molecular grade index (MGI),comprising summing the expression levels of Bub1B, CENPA, NEK2,RACGAP1, and RRM2 using coefficients determined from principal component analysis of the dataset; and(iv) linearly combining or having linearly combined the H:I and the MGI as continuous variables;(b) selecting or having selected a BCI cutoff, wherein the BCI cutoff is or has been selected such that the risk of cancer recurrence is less than 5% for a BCI below the BCI cutoff;(c) calculating or having calculated a BCI for the human subject who has been diagnosed with breast cancer and is receiving or has received an initial treatment, comprising:(j) measuring or having measured mRNA expression levels of the genes homeobox B13 (HoxB13), interleukin 17 receptor B (IL17BR), budding uninhibited by benzimidazoles 1 beta (Bub1B), centromere protein A, isoform a (CENPA), never in mitosis gene a-related kinase 2 (NEK2), Rac GTPase activating protein 1 (RACGAPI), and ribonucleotide reductase M2 (RRM2) HoxB13, IL17BR, Bub1B, CENPA, NEK2, RACGAP1, and RRM2 in a sample from the subject comprising ER+ breast cancer cells that are estrogen receptor positive (ER+);(ji) determining or having determined the ratio of expression levels of HoxB13/IL17BR (H:I) of the subject;(iii) calculating or having calculated an MGIof the subject, comprising summing the expression levels of Bub1B, CENPA, NEK2, RACGAP1, andRRM2, wherein the summing uses using coefficients determined from principal component analysis of the dataset; and(iv) calculating or having calculated a breast cancer index (BCI) value by linearly combining or having linearly combined H:I and MGI as continuous variables; (_) comparing or having compared the BCIvalue of the subject to [[a]] the BCI cutoff, wherein the BCI cutoff is or has been selected such that the risk of cancer recurrence is less than 5% for a BCI below the BCI cutoff; (e) classifying or having classified the subject into a two-category scheme of (a) high risk of recurrence if the subject's BCI is higher than the BCI cutoff or (b) low risk of recurrence if the BCI is lower than the BCI cutoff, wherein classification does not include an intermediate risk category; and f) treating the subject with an adjuvant therapy selected from an aromatase inhibitor, anti-mTOR therapy, anti-HER2 therapy, and endocrine therapy; wherein (a) if the subject has a high risk of recurrence, the subject is treated with the adjuvant therapy for more than 5 years after the initial treatment, [[or]]and (b) if the subject has a low risk of recurrence, the subject is treated with the adjuvant therapy for 5 years or less after the initial treatment..
The claims of 380 are drawn to a method of treating breast cancer in a subject who has undergone removal of ER+ breast cancer and has been treated with a first endocrine therapy of a selective estrogen receptor modulator (SERM), a selective estrogen receptor down-regulator (SERD), or an aromatase inhibitor (AI), the method comprising: preparing cDNA from nucleic acids in a sample of ER+ breast cancer cells from the subject, measuring the expression level of the HoxB13, IL17BR, BubiB, CENPA, NEK2, RACGAP], and RRM2 genes from said cDNA, calculating a ratio of expression levels of HoxB13:IL]7BR ("H:I ratio"), and a summation value of expression levels of BubiB, CENPA, NEK2, RACGAPI, and RRA2 using the subject's expression levels, combining the H:I ratio with the summation value to obtain a subject index value, comparing the subject index value to a reference index value for ER+ breast cancer patients that did not have cancer recurrence and/or ER+ breast cancer patients that did have cancer recurrence, classifying the subject as having a high risk of recurrence of breast cancer if the subject's index value is (a) above the reference index value for the patients that did not have cancer recurrence and/or (b) not below the reference index value for the patients that did have cancer recurrence, and treating the subject classified as having a high risk of recurrence with a second endocrine therapy.
Ma (PCA) teaches, “Without loss of generality, we use genomic study with gene expression measurements as a representative example but note that analysis techniques discussed in this article are also applicable to other types of bioinformatics studies. Principal component analysis (PCA) is a classic dimension reduction approach. It constructs linear combinations of gene expressions, called principal components (PCs). The PCs are orthogonal to each other, can effectively explain variation of gene expressions, and may have a much lower dimensionality. PCA is computationally simple and can be realized using many existing software packages.” (abstract). Ma (PC) teaches, “PCA is one of the oldest dimension reduction approaches [3, 4]. It searches for linear combinations of the original measurements called principal components (PCs) that can effectively represent effects of the original measurements. PCs are orthogonal to each other and may have dimensionality much lower than that of the original measurements. Because of its computational simplicity and satisfactory statistical properties, PCA has been extensively used in multiple statistical areas. Most recently, it has been used in bioinformatics studies, particularly gene expression studies, to reduce the dimensionality of high-throughput measurements” (page 715, 1st column, 2nd paragraph). Ma (PCA) teaches, “For example, in cancer prognosis studies , less than 10 PCs can be sufficient to represent pathways composed of hundreds of genes.(page 717, 1st paragraph).
Thus it would have prima facie obvious to one of ordinary skill in the art prior to the effective date of the claims to use PCA to determine coefficient for BCI calculation. The artisan would be motivated as Ma (PCA) teaches, “For example, in cancer prognosis studies , less than 10 PCs can be sufficient to represent pathways composed of hundreds of genes.(page 717, 1st paragraph).The artisan would be motivated as the claims are commensurate in scope.
The dependent claims are rejected as they are coextensive in scope.
Response to Arguments
The response traverses the rejection in view of the amendment to provide an “and” between the two conditional treatment steps. This argument has been thoroughly reviewed but is not considered persuasive as the second alternative treatment of 380 still encompass the treatments of the instant claims.
Claims 21, 22-27, 29-30, 32-33 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-15 of U.S. Patent No. 11,078,538 in view of Ma(BRIEFINGS IN BIOINFORMATICS. VOL 12. NO 6. 714 -722 doi:10.1093/bib/bbq090 Advance Access published on 17 January 2011.) is being referred to as Ma (PCA). Although the claims at issue are not identical, they are not patentably distinct from each other because they are coextensive in scope.
The instant claims are drawn to A method of treating a human subject who has been diagnosed with breast cancer and is receiving or has received an initial treatment, the method comprising the steps of: (a) calculating or having calculated a breast cancer index (BCI) for a dataset of human subjects having estrogen receptor positive (ER+) breast cancer, comprising:(i) measuring or having measured mRNA expression levels of the genes homeobox B13 (HoxB13), interleukin 17 receptor B (IL17BR), budding uninhibited by benzimidazoles 1 beta (Bub1B), centromere protein A, isoform a (CENPA), never in mitosis gene a-related kinase 2 (NEK2), Rac GTP activating protein 1 (RACGAP1), and ribonucleotide reductase M2 (RRM2) of the dataset subjects;(ii) determining or having determined the ratio of expression levels of HoxB13IL17BR (H:I );(iii) calculating or having calculated a molecular grade index (MGI),comprising summing the expression levels of Bub1B, CENPA, NEK2,RACGAP1, and RRM2 using coefficients determined from principal component analysis of the dataset; and(iv) linearly combining or having linearly combined the H:I and the MGI as continuous variables;(b) selecting or having selected a BCI cutoff, wherein the BCI cutoff is or has been selected such that the risk of cancer recurrence is less than 5% for a BCI below the BCI cutoff;(c) calculating or having calculated a BCI for the human subject who has been diagnosed with breast cancer and is receiving or has received an initial treatment, comprising:(j) measuring or having measured mRNA expression levels of the genes homeobox B13 (HoxB13), interleukin 17 receptor B (IL17BR), budding uninhibited by benzimidazoles 1 beta (Bub1B), centromere protein A, isoform a (CENPA), never in mitosis gene a-related kinase 2 (NEK2), Rac GTPase activating protein 1 (RACGAPI), and ribonucleotide reductase M2 (RRM2) HoxB13, IL17BR, Bub1B, CENPA, NEK2, RACGAP1, and RRM2 in a sample from the subject comprising ER+ breast cancer cells that are estrogen receptor positive (ER+);(ji) determining or having determined the ratio of expression levels of HoxB13/IL17BR (H:I) of the subject;(iii) calculating or having calculated an MGIof the subject, comprising summing the expression levels of Bub1B, CENPA, NEK2, RACGAP1, andRRM2, wherein the summing uses using coefficients determined from principal component analysis of the dataset; and(iv) calculating or having calculated a breast cancer index (BCI) value by linearly combining or having linearly combined H:I and MGI as continuous variables; (_) comparing or having compared the BCIvalue of the subject to [[a]] the BCI cutoff, wherein the BCI cutoff is or has been selected such that the risk of cancer recurrence is less than 5% for a BCI below the BCI cutoff; (e) classifying or having classified the subject into a two-category scheme of (a) high risk of recurrence if the subject's BCI is higher than the BCI cutoff or (b) low risk of recurrence if the BCI is lower than the BCI cutoff, wherein classification does not include an intermediate risk category; and f) treating the subject with an adjuvant therapy selected from an aromatase inhibitor, anti-mTOR therapy, anti-HER2 therapy, and endocrine therapy; wherein (a) if the subject has a high risk of recurrence, the subject is treated with the adjuvant therapy for more than 5 years after the initial treatment, [[or]]and (b) if the subject has a low risk of recurrence, the subject is treated with the adjuvant therapy for 5 years or less after the initial treatment..
A method of treating breast cancer in a subject who has undergone removal of estrogen receptor positive (ER+) breast cancer and has been treated with a first endocrine therapy of a selective estrogen receptor modulator (SERM), a selective estrogen receptor down-regulator (SERD), or an aromatase inhibitor (AI), the method comprising: preparing cDNA from nucleic acids in a sample of ER+ breast cancer cells from the subject, measuring the expression level of the HoxB13, IL17BR, Bub1B, CENPA, NEK2, RACGAP1, and RRM2 genes from said cDNA, calculating a ratio of expression levels of HoxB13:IL17BR (“H:I ratio”) using the subject's expression levels, calculating a molecular grade index (“MGI”) comprising summing expression levels of Bub1B, CENPA, NEK2, RACGAP1, and RRM2 using the subject's expression levels, building a continuous risk model by combining an H:I ratio and a MGI as continuous variables from a plurality of reference patients, establishing a reference breast cancer index (BCI) value for ER+ breast cancer patients that did not have cancer recurrence and/or ER+ breast cancer patients that did have cancer recurrence by combining the H:I ratio and MGI from the plurality of reference patients, wherein the reference BCI value has a cut-off value greater than 6.4, calculating the subject's BCI value by combining the subject's H:I ratio and MGI, comparing the subject's BCI value to the cut-off value, classifying the subject as having recurrence of breast cancer if the subject's BCI value is (a) above 6.4 for the patients that did not have cancer recurrence and/or (b) not below 6.4 for the patients that did have cancer recurrence, wherein risk of cancer recurrence is higher above the cut-off than below the cut-off, and treating the subject classified as having a high risk of recurrence with a second endocrine therapy.
Ma (PCA) teaches, “Without loss of generality, we use genomic study with gene expression measurements as a representative example but note that analysis techniques discussed in this article are also applicable to other types of bioinformatics studies. Principal component analysis (PCA) is a classic dimension reduction approach. It constructs linear combinations of gene expressions, called principal components (PCs). The PCs are orthogonal to each other, can effectively explain variation of gene expressions, and may have a much lower dimensionality. PCA is computationally simple and can be realized using many existing software packages.” (abstract). Ma (PC) teaches, “PCA is one of the oldest dimension reduction approaches [3, 4]. It searches for linear combinations of the original measurements called principal components (PCs) that can effectively represent effects of the original measurements. PCs are orthogonal to each other and may have dimensionality much lower than that of the original measurements. Because of its computational simplicity and satisfactory statistical properties, PCA has been extensively used in multiple statistical areas. Most recently, it has been used in bioinformatics studies, particularly gene expression studies, to reduce the dimensionality of high-throughput measurements” (page 715, 1st column, 2nd paragraph). Ma (PCA) teaches, “For example, in cancer prognosis studies , less than 10 PCs can be sufficient to represent pathways composed of hundreds of genes.(page 717, 1st paragraph).
Thus it would have prima facie obvious to one of ordinary skill in the art prior to the effective date of the claims to use PCA to determine coefficient for BCI calculation. The artisan would be motivated as Ma (PCA) teaches, “For example, in cancer prognosis studies , less than 10 PCs can be sufficient to represent pathways composed of hundreds of genes.(page 717, 1st paragraph).The artisan would be motivated as the claims are commensurate in scope.
The dependent claims are rejected as they are coextensive in scope.
Response to Arguments
The response traverses the rejection in view of the amendment to provide an “and” between the two conditional treatment steps. This argument has been thoroughly reviewed but is not considered persuasive as the second alternative treatment of 380 still encompass the treatments of the instant claims.
Summary
No claims are allowed.
Conclusion
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/Steven Pohnert/Primary Examiner, Art Unit 1683
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