DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This action is in response to the papers filed November 6, 2025. Applicant’s remarks and amendments have been fully and carefully considered but are not found to be sufficient to put the application in condition for allowance. Any new grounds of rejection presented in this Office Action are necessitated by Applicant's amendments. Any rejections or objections not reiterated herein have been withdrawn. This action is made FINAL.
Claims 74-79 and 82-86 are currently pending and have been examined herein.
Claim Rejections - 35 USC § 112
3. 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 74-79 and 82-86 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.
Claims 74-79 and 82-86 are rejected for referring to specific figures and/or tables in the specification. MPEP 2173.05(s) states that “Where possible claims are to be complete in themselves. Incorporation by reference to a specific figure or table “is permitted only in exceptional circumstances where there is no practical way to define the invention in words and where it is more concise to incorporate by reference than duplicating a drawing or table into a claim. Incorporation by reference is a necessity doctrine, not for applicant’s convenience.”
Claim Rejections - 35 USC § 112(a)
4. 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 74-79 and 82-86 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 enablement requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention.
The claims are drawn to a method of treating a patient having an activated B cell (ABC) cell of origin (COO) diffuse large B cell lymphoma (DLBCL).
The claims recite a step of identifying the COO of the DLBCL as ABC.
The claims recite a step of extracting DNA from a sample from the patient.
The claims recite a step of amplifying the extracted DNA.
The claims recite a step of sequencing the amplified DNA to acquire a list of genomic features associated with the sample.
The claims recite a step of “applying” by a computer, a COO DNA classification (COODC) machine learning model to the list of genomic features to calculate a probability score, wherein the COODC machine learning model comprises a selected set of DNA-based features including each of the features described in Table 1
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wherein the probability score is above, or equal to, a pre-defined cutoff, thereby identifying the patient as having an ABC COO.
The claims recite a step of administering an effective amount of a BCR signaling inhibitor to the patient, thereby treating the patient identified as having the ABC COO DLBCL.
Due to the vagueness of the recited “features” in Table 1, the claims potentially encompass a large genus of “features” that are correlated with ABC. The claims do not define any particular “features” that are correlated with ABC. The claims do not describe the COODC model nor do they describe how to calculate the probability score. The claims do not set forth what the pre-defined cutoffs are.
The nature of the invention requires a reliable correlation between genomic features and the ABC cell of origin of a DLBCL.
Teachings in the Specification and Examples
The specification (para 0010) teaches a method of determining the cell of origin (COO) of diffuse large B Cell lymphoma (DLBCL) using a cell of origin DNA classification (COODC). The specification teaches applying a pre-defined COODC classifier to a list of genomic features (e.g., one or more features described in Table 1) to calculate a predictor score. Table 1 is partially reproduced below:
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While Table 1 lists genomic features, the skilled artisan reading this table would have no idea what structures these genomic features have. Table 1 does not provide information necessary for the skilled artisan to make and/or use the presently claimed method.
The specification [0050] teaches that 482 DLBCL samples from the GOYA study that had DNA sequenced using FoundationOne®Heme were split into two sets: ⅔ into a training set and ⅓ into a held-out validation set. The training set was further subset to include only samples with either an ABC or GCB call as determined by Nanostring; unclassified samples or samples without a call were excluded. The held-out validation set was used after the model was complete to determine concordance. The training set data were then used to train a penalized logistic regression model to identify ABC or GCB samples using DNA-based features without the need for RNA. 594 features were available to train the model, including binary features of any alteration in a gene, specific alterations (codons), and hotspot alterations (any one of multiple codons) that occurred at least 5 times in the GOYA dataset as well as derived DNA-based features such as tumor mutational burden (TMB), chromosome arm-level copy number and zygosity metrics, and frequency of alteration classes (e.g., T mutated to A). Per-sample probabilities were extracted from the model, and a pair of cutoffs was chosen to optimize sensitivity and specificity, with particular focus on optimizing ABC accuracy. This model is herein referred to as the Cell of Origin DNA Classifier (COODC; the classifier is also referred to herein, e.g., as a method, model and assay). The COODC model contained a total of 74 genomic features and generated a continuous probability score of a sample being ABC ranging from 0 to 0.999. The 74 genomic features included 18 arm-level alteration features, including copy number and loss of heterozygosity features, 32 gene short variant features, 6 rearrangement-based features, 13 gene-level features (including copy number, rearrangement, and short variant alterations) and various other summary features (including T>A mutation prevalence).
State of the Art and the Unpredictability of the Art
While methods of sequencing DNA to acquire genomic features associated with a sample are known in the art, methods of using genomic features to classify disease subtypes (such as classifying DLBCL as ABC) are highly unpredictable. The unpredictability will be discussed below.
Swennen (Belg J Hematol 2018;9(6):206-213) teaches that diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma type worldwide, but the treatment still remains challenging because only 60-70% of the patients can be cured with the standard immunochemotherapy (rituximab, cyclophosphamide-doxorubicin-vincristine-prednisone) scheme. In the last twenty years, several molecular-genetic studies showed that DLBCL comprises at least two distinct molecular subtypes: the activated B-cell-like and the germinal center B-cell-like subtype. The two groups have different genetic mutation landscapes and outcomes following treatment, with the ABC subtype having the worst prognosis. Gene expression profiling seems to be the gold standard method to subdivide DLBCL into ABC and GCB subtypes, but it is difficult to include this technology in clinical practice because it relies on fresh frozen tissue and microarray technology. To facilitate the DLBCL classification in daily clinical practice, other technologies have been developed allowing analysis of formalin-fixed paraffine embedded tissue biopsies (abstract). Swennen discloses mutations which can be used to classify cell of origin of DLBCL (see Table 1 reproduced below).
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Based on the teachings of Swennen it is clear that classifying DLBCL based on cell of origin by detecting mutations was known in the art. However, the claims are rejected from an enablement standpoint because it is unclear from the specification which other genomic features can be used to cluster DLBCL based on cell of origin. As discussed above the claims do not define the genomic features in terms of their structure. Table 1 lists 74 genomic features which can be used to distinguish GCB from ABC, however the skilled artisan reading this table would have no idea what structures these genomic features have. Table 1 does not provide information necessary for the skilled artisan to make and/or use the presently claimed method.
The claims require applying a COO DNA classification model to the list of genomic features to calculate a probability score. The claims do not set forth how the “ probability score” is calculated. The specification teaches a classification model used but does not provide any other information regarding the algorithm and without this information, the skilled artisan would not be able to make and/or use the claimed invention because they would not know how to calculate the probability score.
Quantity of Experimentation:
In the instant case one of skill in the art could not practice the full scope of the invention because the specification does not provide the guidance necessary to classify the DLBCL as a ABC. In particular the specification does not disclose the structure of the genomic features which should be used in the claimed method. Further the specification does not disclose how the probability score is calculated from the genomic features. These two aspects are critical to the claimed methodology. The breadth of the current claims could only be practiced after performing additional experimentation.
Applicant’s attention is directed to Wyeth v. Abbott Laboratories 107 USPQ2d 1273, 1275, 1276 (Fed. Cir. June 2013) wherein it is stated that “Claims are not enabled when, at the effective filing date of the patent, one of ordinary skill in the art could not practice their full scope without undue experimentation. MagSil Corp. v. Hitachi Global Storage Techs., Inc., 687 F.3d 1377, 1380-81 [103 USPQ2d 1769] (Fed. Cir. 2012).” Therein, it was held that even routine experimentation may be undue when it is extensive and the results are unpredictable.
Case law has established that '(t)o be enabling, the specification of a patent must teach those skilled in the art how to make and use the full scope of the claimed invention without ‘undue experimentation.'" In re Wright 990 F.2d 1557, 1561. In re Fisher, 427 F.2d 833, 839, 166 USPQ 18, 24 (CCPA 1970) it was determined that '(t)he scope of the claims must bear a reasonable correlation to the scope of enablement provided by the specification to persons of ordinary skill in the art". The amount of guidance needed to enable the invention is related to the amount of knowledge in the art as well as the predictability in the art. Furthermore, the Court in Genetech Inc. v Novo Nordisk 42 USPQ2d 1001 held that '(I)t is the specification, not the knowledge of one skilled in the art that must supply the novel aspects of the invention in order to constitute adequate enablement".
Further, as set forth in Rasmusson v. SmithKline Beecham Co., 75 USPQ2d 1297, 1302 (CAFC 2005), enablement cannot be established unless one skilled in the art "would accept without question" an Applicant's statements regarding an invention, particularly in the absence of evidence regarding the effect of a claimed invention. Specifically:
"As we have explained, we have required a greater measure of proof, and for good reason. If mere plausibility were the test for enablement under section 112, applicants could obtain patent rights to "inventions consisting of of little more than respectable guesses as to the likelihood of their success. When one of the guesses later proved true, the “inventor” would be rewarded the spoils instead of the party who demonstrated that the method actually worked. That scenario is not consistent with the statutory requirement that the inventor enable an invention rather than merely proposing an unproved hypothesis."
Conclusions:
Herein, although the level of skill in the art is high, given the lack of disclosure in the specification and in the prior art and the unpredictability of the art, it would require undue experimentation for one of skill in the art to make and use the invention as broadly claimed.
Response To Arguments
5. In the response the Applicants traversed the rejection under 35 USC 112(a) (Enablement). The Applicants argue that the pending claims have been amended to require the features of the model comprise each of the features described in Table 1. These features would have been clearly understood by a skilled artisan, and the specification clearly describes how to use the set of features to determine whether the COO of a DLBCL of a patient was ABC; see, e.g., Examples 3 and 6 of the application as filed. They argue that the COODC machine learning model of the present claims is clearly defined, and that a skilled artisan could have readily practiced the presently claimed subject matter based on the teachings of the specification, without undue experimentation.
This argument and the amended claims have been fully considered but do not overcome the rejection. Based on the teachings in the specification (para 0050), it is clear that the inventors developed a classification model that identifies ABC COO DLBCL based on “features”. Based on the teachings in the specification it is clear that the COODC model contained a total of 74 genomic features and included 18 arm-level alteration features, including copy number and loss of heterozygosity features, 32 gene short variant features, 6 rearrangement-based features, 13 gene-level features (including copy number, rearrangement, and short variant alterations) and various other summary features (including T>A mutation prevalence). The features that are disclosed in Table 1 are written in shorthand and it is not clear what they are. The identity of the “features” that are used in the classification model are critical to the claimed method which requires being able to identify COO of DLBCL because only specific “features” are expected to be able to classify DLBCL samples as having the ABC COO. Due to the lack of guidance in the specification regarding the “features” that work, the skilled artisan would not be able to make and use a model that identifies ABC COO based on “features” without undue experimentation. The Applicants argue that these features would be understood by the skilled artisan but they have provided no evidence that this is true. For these reasons, the specification does not provide an adequate description of the “features” in Table 1 in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention. As such the rejection is maintained.
6. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMANDA HANEY whose telephone number is (571)272-8668. The examiner can normally be reached Monday-Friday, 8:15am-4:45pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Wu-Cheng Shen can be reached on 571-272-3157. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AMANDA HANEY/Primary Examiner, Art Unit 1634