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 .
The claims dated 8/12/2025 are under consideration.
The amendments and arguments presented in the papers filed 8/12/2025 ("Remarks”) have been thoroughly considered. The issues raised in the Office action dated 2/12/2025 listed below have been reconsidered as indicated.
a) The amendments to the specification addressing trade name or mark usage is acknowledged.
b) The objection of claim 51 is rendered moot by the amendments to the claim.
c) The rejections of claims 51, 53, 58-61, 68-69, 76-77, 85 and 86 under 35 U.S.C. 101 are withdrawn because the sequencing of polynucleotides captured using different bait oligonucleotides that collectively hybridize to at least 500 target genomic regions generates a large amount of sequence data which is then analyzed by a trained classifier is of such complexity that it cannot feasibly be carried out by the human mind even with the aid of pen and paper.
d) The rejections of: claim(s) 51, 53, 59, 68, 69 and 85 under 35 U.S.C. 102(a)(1) and 102(a)(2) as anticipated by or, in the alternative, under 35 U.S.C. 103 as obvious over Meissner (WO 2018/209361 A2); claim(s) 58, 60 and 61 under 35 U.S.C. 103 as obvious over Meissner (WO 2018/209361 A2) in view of Gross (WO 2019/195268; cited on the 2/22/2022 IDS); and claim(s) 86 under 35 U.S.C. 103 as obvious over Meissner (WO 2018/209361 A2) in view of Stamatoyannopoulos (US 2016/0004814 A1), are withdrawn in view of the amendments to the claims.
The Examiner’s responses to the Remarks regarding issues not listed above are detailed below in this Office action.
New and modified grounds of rejection necessitated by amendment are detailed below and this action is made FINAL.
Election/Restrictions
Applicant elected without traverse Group II, claims 51, 53, 58, 59, 60, 61, 68, 69, 76, 77, 78, 85 and 86, in the reply filed on 12/10/2024.
New claims 127-135 depend from claim 51 and are included with elected Group II.
Claims 1-4, 34, 35, 44-45, 83, 84, 95 and 110 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 12/10/2024.
Applicant’s election without traverse of List 8, SEQ ID NOs: 34,881-57,336, in the reply filed on 12/10/2024 is acknowledged.
Claim 78 is withdrawn because a review of SEQ ID NOs from Lists 2, 3, 5, 6 and 8 as identified in Table 1 found that each list has Sequences that are different from the other lists. Applicant did not identify by SEQ ID NOs which sequences from the 22,456 sequences of List 8 are also found in Lists 2, 3, 5 and 6.
Priority
Priority to PCT/US2020/016673 is recognized.
Priority to PCT/US2020/015082 is not fully recognized because it does not disclose the sequences of the present application.
Priority to 62/8010,556 is not recognized because it does not disclose methods using “bait oligonucleotides” or that the “bait oligonucleotides” “collectively hybridize to at least 500 target genomic regions” as required by claim 51 and does not disclose any sequences identified with SEQ ID NOs.
Priority to 62/801561 is not recognized because it does not disclose methods for detecting cells of a hematological disorder, using “bait oligonucleotides” or that the “bait oligonucleotides” “collectively hybridize to at least 500 target genomic regions” as required by claim 51 and does not disclose any sequences identified with SEQ ID NOs.
Priority to 62/965,327 is not fully recognized because List 8 is not disclosed as required by claims 76 and 77.
Priority to 62/965,342 is not recognized because it does not disclose methods for detecting cells of a hematological disorder or target genomic regions that are differentially methylated in at least one HD relative to a different HD or relative to a non-HD cancer as required by claim 51 and does not disclose all the sequences of at least presently disclosed and claimed List 8.
The earliest effective priority date recognized is 2/4/2020.
Information Disclosure Statement
The listing of references in the specification is not a proper information disclosure statement. 37 CFR 1.98(b) requires a list of all patents, publications, or other information submitted for consideration by the Office, and MPEP § 609.04(a) states, "the list may not be incorporated into the specification but must be submitted in a separate paper." Therefore, unless the references have been cited by the examiner on form PTO-892 or cited on a submitted IDS, they have not been considered.
Drawings
High resolution copies of the drawings may be accessed via PAIR/Patent Center Retrieval using the Supplemental Content tab.
Specification
The following is a new objection.
The disclosure is objected to because of the following informalities: the amendments in paragraph [0001] do not match the most recent ADS and the filing receipt dated 11/26/2021, which claims benefit to 62/801,556.
Appropriate correction is required.
Claim Interpretation
The term “cell-free DNA” or “cfDNA” is interpreted in view of para. 74 of the instant specification which explicitly defines the term.
Terms recited within parentheticals are being interpreted as being abbreviations for the elements proceeding them, e.g. HD is an abbreviation for “hematological disorder” and cfDNA is an abbreviation for “cell-free DNA”.
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 51, 53, 58-61, 68-69, 76-77, 85, 86 and 127-137 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.
Regarding claim 51, the claim broadly encompasses detecting the first HD with a trained classifier using information from the sequencing data obtained from polynucleotides captured using different bait oligonucleotides that collectively hybridize to at least 500 target regions. The claim specifies the target genomic regions were “differentially methylated in at least one HD relative to a different HD or relative to a non-HD cancer”
The instant specification does not identify any combination of 500 target genomic regions make up a functional “trained classifier”. In regards to List 8, which is 22,456 target genomic regions, the instant specification analyzed random sets of 25% or 50% of the genomic regions of List 8, which equates to 5,614 and 11,228 genomic regions. Sets of 25% from List 8 have ~11-fold more genes than that of a classifier trained on and analyzing sets of 500 target genomic regions. Stated differently, 500 target genomic regions represents only 2.22% of all the genes of List 8.
Sets of target genomic regions and their corresponding “trained classifiers” that are this small are not identified by the specification, nor are tools for identifying such sets that are functional in the context of detecting cells of a HD within the context of those Lists have thousands of target genomic regions. While the claim states that 500 target genomic regions may be used in a classifier, no representative species of such a set is provided. For example, no representative species encompassed of panel of 500 target genomic regions for “all target hematological disorders”, lymphoid neoplasm and myeloid, as the specification describes combinations that includes over a thousand to several thousand target genomic regions. The ordinary artisan would not have found applicant to be in possession of functional sets of 500 target genomic regions or “trained classifiers” based on the status of 500 genomic regions, in particular for “all target hematological disorders, lymphoid and myeloid neoplasms.
Table 1 lists exemplary sets of target genomic regions. Lists 1 and 8 are related in that List 8 is a narrowed subset of List 1 and both are used to target “all” hematological disorders. List 8 represents 79.8% of List 1. There is no indication of a representative species of a subset of 500 target genomic regions that can be used to detect “all” hematological disorders.
List 5 is a narrowed subset of List 2 and both are used to target lymphoid neoplasms. List 5 represents 80.9% of list 2. There is no indication of a representative species of a subset of 500 target genomic regions that can be used to detect a lymphoid neoplasm.
List 6 is a narrowed subset of List 3 and both are used to target multiple myeloma. List 6 represents 93.5% of list 3. There is no indication of a representative species of a subset of 500 target genomic regions that can be used to detect a multiple myeloma.
List 7 is a narrowed subset of List 4 and both are used to target myeloid neoplasm. List 7 represents 93.8% of list 4. There is no indication of a representative species of a subset of 500 target genomic regions that can be used to detect a myeloid neoplasm. In the exemplary sets of target genomic regions in Table 1, subsets of target genomic regions presenting well over 50% of the target genomic regions were utilized. None of these representative species extrapolate to sets of target genomic regions that represent smaller proportions of the target genomic regions, such as less than 10% of the target genomic regions identified in the lists.
Claim 51 further encompasses any and all combinations of 500 target genomic regions, beyond those exemplified in Table 1. The instant specification relies on an analysis of whole-genome bisulfite sequencing, which provides methylation information from across the entire genome that was sampled. If any additional target genomic regions exist, the analysis of the specification should have identified them. There is no guidance as to whether any additional target genomic regions exist or how to extrapolate those disclosed to identifying additional target genomic regions, that for example detect lymphoid neoplasms or all hematological disorders. Thus, the applicant has not demonstrated the possession or the existence of any additional target genomic regions that may be used in the claimed method for detecting.
Claim 53 broadly encompasses target genomic regions that are 2,000 to 20,000 nucleotides in size (e.g., 100 target genomic regions covering 200,000 to 2 million nucleotides). The target genomic regions identified in Lists 1-8 are significantly shorter than this. There is no clear description of any sequences for target genomic regions covering 2,000 to 20,000 nucleotides. Furthermore, cfDNA is fragmented genomic DNA with a size that significantly smaller than 20,000 nucleotides or even 2,000 nucleotides. There is no indication that applicant possessed sets of 500 target genomic regions with an average combined size of 2,000 to 20,000 nucleotides. Also, as previously noted, the instant specification relies on an analysis of whole-genome bisulfite sequencing, which provides methylation information from across the entire genome that was sampled. There is no indication of any additional target genomic regions that would contribute another 198,000 to nearly 2 million nucleotides and that are informative in detecting a hematological disorder.
The claims broadly encompass the use of at least 500 target genomic sequences from List 8, which covers SEQ ID NOs: 34881-57336. A review of the sequences indicates that numerous sequences are duplicates of one another. For example SEQ ID NO: 42,207 and SEQ ID NO: 35,481 are identical and both map to chr2:9144127-9144172; however, SEQ ID NO: 42,207 is identified as being “hypo” and SEQ ID NO: 35,481 is identified as being “hyper”, in the Sequence Listing. SEQ ID NO: 36,081 and SEQ ID NO: 43,933 are identical and both map to chr3:160473309-160473405; however, SEQ ID NO: 36,081 is identified as being “hyper” and SEQ ID NO: 43,933 is identified as being “hypo”, in the Sequence Listing. The instant specification does not describe what differences contribute to one sequence being “hypermethylated” versus one being “hypomethylated”, because the exact same sequence is provided for both methylation states.
The instant specification does not describe in what context these sequence are “hyper” (understood to be “hypermethylated”) versus “hypo” (understood to be “hypomethylated”). The instant specification does not identify what distinguishes “hypermethylated” from “hypomethylated” and since the sequences are identical, it is unclear what positions are or are not methylated in order to detect a cell of a particular HD. The is no guidance as to how the classifier is to use this generic genomic target sequence to be determine a methylation state as being “hypermethylated” versus “hypomethylated”. The specification does not identify whether such a sequence is relevant to detecting lymphoid neoplasm, multiple myeloma, myeloid neoplasm, etc. The instant specification does not identify which sequences or their methylation states of Table 1 that are relevant to detecting leukemia cells. The application does not adequately describe the relevancy of the sequences disclosed in Table 1.
The claims as amended require the analysis of sequencing reads from differentially methylated regions such that: i) the trained classifier assigns a score for the first HD based on the sequencing reads produced by the sequence of the captured polynucleotides; ii) the score is a measure of (1) likelihood of obtaining the sequencing reads in a sample from a subject without the first HD, and (2) similarity of the at least 500 target genomic regions in the subject as compared to the at least 500 target genomic regions in the reference subjects with the first HD; and iii) the score is above a threshold for detecting presence of the cells of the first HD. The method as claimed does not provide any feature that leads to the sequencing data having information about methylation status. Applicant does not have possession of a classifier that analyzes differentially methylated regions and detects a first HD based on sequences providing no methylation information. For example, the target genomic region sequences captured by the bait oligonucleotides are present in all cfDNA and simply detecting the sequences, such as SEQ ID NO: 42,207, provides no information regarding a particular HD when the classifier disclosed relies on methylation data.
In summary, the limited number of embodiments presented in the specification and the generic information about target genomic regions (being both “hypomethylated” and “hypermethylated”) does not demonstrate possession of the full scope of embodiments encompassed by the generic claims.
Response to the traversal of the written description rejections
The Remarks summarize the amendments and characterize the teachings of the specification (p. 17).
The Remarks have been fully considered but are not persuasive. The examiner’s position is detailed above. While the instant specification generically states that 500 target genomic regions may be used, the analysis in the specification did not identify any classifiers based on 500 target genomic regions, in particular for classifiers trained on all target hematological disorders. Various numbers and locations of target genomic sequences were identified based on the type of hematological disorders, e.g., 1447 and 1170 for lymphoid neoplasms and 28,130 and 22,456 for all “targeted hematological disorders”. It is noted the full scope of “all” hematological disorders is not identified by the specification. Based on these findings, the specification demonstrates that it is unpredictable as to what target genomic regions and how many are relevant to identifying a hematological disorder, or a specific type of hematological disorder. The instant specification also demonstrates that a large proportion of genomic regions screened across all genomic DNA in a whole genome bisulfite sequencing assay were not relevant to detecting hematological disorder. There is no guidance that differentiates those regions identified in the specification from those that were not useful or informative in the context of detecting a hematological disorder or in the context of identifying a particular hematological disorder from a different hematological disorder.
With regards to the specification stating the performance of small panels in terms of size in kb, i.e., less than 500 kb, are sufficient, it is noted that size of the panels based on the number of nucleotides covered does not identify the number of CpG sites that are informative or the number of target genomic regions that are represented by that “small panel” size. For example, even though List 2 and 3 cover 403 and 277 kbs, they still cover 1,447 target genomic region and 879 target genomic regions, respectively. There is no direct correlation between the size of the panel in KB and the number of target genomic regions covered. For example, while List 5 has less target genomic regions than List 2, its panel size is larger; despite both List being used for the identification of Lymphoid neoplasms.
With the regards to random selection of target regions within the specification, this was done in the context of List 8, which has 22,456 target genomic regions. The random sets of 25% or 50% of the genomic regions of List 8 have 5,614 and 11,228 genomic regions, respectively. Panels of 500 target genomic regions omit a large majority target genomic regions for List 8 and subsets of 25% and 50% of the genomic regions. There are no indications that a functional classifier can be developed based on 500 target genomic regions for any all types of HDs, and if so, which 500 target genomic regions are functional at this reduced number versus those that are not functional.
The Remarks argue the present application also teaches that thresholds can be adjusted and target genomic regions may be selected "to maximize classification accuracy, subject to a size budget” (p. 18). The Remarks further argue a person of ordinary skill in the art would reasonably conclude that Applicant had successfully identified "at least 500 target genomic regions" useful in detecting cells of hematological disorders, expressly contemplated using fewer than the full collections described for illustrative purposes when subject to further constraints, and provided results indicating that using subsets nonetheless permitted such detection (p. 18).
The arguments have been full considered but are not persuasive. The generic guidance does not lead one to identify any set of 500 or 600 genomic target regions of applicant had possession of. The analyses performed in the specification demonstrate that the number of target genomic regions varies between hematological disorders, that substantially more genomic target regions were identified as being utilized for detection of a particular hematological disorder and that a large swarth of genomic regions were not applicable to detecting hematological disorder. Regarding the last point, as noted previously, whole genome bisulfite sequencing was used for identifying informative genomic regions, yet a minority of sequences were identified as target genomic regions.
The Remarks argue present application teaches how to identify differentially methylated regions for different kinds of hematological disorders, and how to use them to train a classifier and its use in the detection of hematological disorders in a test subject (p. 18). The Remarks argue the application illustrates this process using particular input data as an example and at no point does the present application indicate that no other markers for the indicated hematological disorders exist (p. 18). The Remarks further argue the skilled person is taught how to apply the processes disclosed in the present application for the detection of additional markers, and that target genomic regions so identified would reasonably be expected to have similar utility in methods according to the present claims (p. 18).
The arguments have been fully considered and are not persuasive. The specification demonstrates the identifying target genomic regions is unpredictably. Whole genome bisulfite sequencing data as analyzed and different sets of genomic regions were identified as target genomic regions depending on the type of hematological disorder. There is no guidance provided as to which additional genomic regions exist, if at all. In regards to the databases analyzed by the specification, the teachings demonstrate that analysis found a number of genomic regions were not informative or useful. Thus, applicant has not demonstrated an interest in or a use for those genomic regions not identified in the examples, in at least for detecting the hematological disorders listed in Table 1.
The Remarks argue the skilled person is also taught how to recognize the structural features of such target genomic regions, in terms of nucleotide content and chemical modification states (p. 18).
The arguments are not persuasive. For example, genomic regions represented in the data set analyzed by the specification demonstrates that is it unpredictable which structures are relevant. It is differential methylation between populations that is relevant. Simply having CpG cites or particular content of A, T, C or G residues is not sufficient. Furthermore, because the particular methylation status, profiles or patterns of the disclosed target genomic regions are not provided, one is not provided with a common or core methylation status, profile or pattern that can be used to readily identify other target genomic regions. For example, a particular genomic region may be relevant to some hematological disorders but not others and the structure of the genomic region provides no guidance as to when and how a genomic region may be used.
The Remarks argue the application as filed reasonably conveys that Applicant was in possession of a method for identifying target genomic regions comprising "a plurality of CpG sites" that are "selected as a marker included in a trained classifier based on differential methylation of the plurality of CpG sites in reference subjects," and how to use sequence information from such sites with a trained classifier to assign a score that is "a measure of (1) likelihood of obtaining the sequencing reads in a sample from a subject without the first HD, and (2) similarity of the at least 500 target genomic regions in the subject as compared to the at least 500 target genomic regions in the reference subjects with the first HD." See p. 19.
The arguments have been fully considered but are not persuasive. The genus of at least 500 target genomic regions and classifiers that produce trained classifiers based on the 500 target genomic regions is substantial in size. The instant specification discloses a limited number of species or embodiments that use and train particular classifiers to identify particular sets of target genomic regions. The panels of target genomic regions are significantly larger in size than 500 target genomic regions. If such panels are feasible and identifiable, the specification should have identified such a panel. This limited number of species is not representative of all other panels of, for example 500 target genomic regions, and the trained classifiers they produce.
The Remarks argue the Office considers increasing target genomic region size as a function of panel size, but this is backward (p. 19). The Remarks argue the present application teaches that "CpG sites scored by this metric are ranked and greedily added to a panel until the panel size budget is exhausted" and provides panels of increasing numbers of target genomic regions, increasing sizes of the genome represented thereby, and teaches their use in combination. The Remarks argue panels that in combination fall within this range are clearly taught by the present application, for example in the lists in Table 1. The Remarks argue a person of ordinary skill in the art would not reasonably interpret the largest panel size as applying to the smallest possible number of targets, and the application need not provide explicit examples within such construction in order to satisfy the written description requirement. When given its broadest reasonable interpretation, the written description requirement is satisfied with regard to the features of claim 53. See p. 19-20.
The arguments are fully considered and are not persuasive. The specification analyzed whole genome bisulfite sequencing data and did not identify any combination of genomic regions that approach the size encompassed by claim 53. Even if all the target genomic regions of Table 1 are included (including the duplicate sequences), only around 5,100 kbs of genomic regions was identified, a fraction of 200 kb encompassed by claim 53.
The Remarks argue the claims are directed to "target genomic sequences," not target SEQ ID NOs. The Remarks argue despite certain sequences being listed more than once (e.g., hypermethylated in a first cancer type and hypomethylated in another cancer type), there would be no confusion about counting such single genomic region only once among the at least 100 target genomic regions. The Remarks argue the application expressly teaches that "[t]he sequence listing identifies the chromosomal location of each target genomic region, whether cfDNA fragments to be enriched from the region are hypermethylated or hypomethylated, and the sequence of one DNA strand of the target genomic region". See p. 20-21.
The arguments have been fully considered but are not persuasive.
Specific target genomic regions are described in Table 1 and identified by SEQ ID NOs. The claims encompasses the use of these target genomic regions. While the claims are drawn to largely generic genomic regions, Table 1 specifically disclose sets of the target genomic regions that are identified by their sequences as represented in SEQ ID NOs. The reference to SEQ ID NOs in the context of those embodiments is appropriate. List 8, specific for all hematological disorders, includes multiple target genomic regions having the exact same genomic sequence identified by different SEQ ID NOs, one being hypomethylated and one being hypermethylated. In the context of all hematological disorders there is no indication whether it is the presence of the hypomethylated or hypermethylated sequence that is relevant to identifying a hematological disorder. A differentially methylated region is either hypomethylated or hypermethylated in a particular context; otherwise it is not a differentially methylated region and the specification does not identify context of methylation that is relevant to hypermethylation or hypomethylated. The target genomic regions of List 8, for example, as applied to the method of claim 1 encompasses using both hypomethylated or hypermethylated as a target genomic regions. But the instant specification does not identify which version is relevant for identifying a particular HD from a different HD.
Furthermore, because the sequences are identical there is no indication what “hypomethylated” versus “hypermethylated” looks like, for example, such that one could design probes that differentiate between the two.
While in general “hypomethylated” versus “hypermethylated” may be appreciated, the terms are relative. The terms are to be understood in particular contexts and as applied to particular methylation profiles identified. For example, claim 133 describes a methylation pattern of five methylation sites that differ between a first HD and a different second HD or non-HD cancer. No methylation profiles are identified in any manner. For example, looking at SEQ ID NO: 1, which is hypermethylated, there is no guidance as to what is the methylation pattern that is relevant to a HD and what is required for it to be “hypermethylated”. Of the 8 CpG sites in SEQ ID NO: 1, there is no indication how many of the site need to be methylated and which ones to identify the sequence as: 1) hypermethylated; and/or 2) having a particular informative methylation pattern. Further, as noted above, there is no guidance as to how to design a bait oligonucleotide that recognizes a particular methylation status of the genomic region corresponding to SEQ ID NO: 1, e.g., hypermethylated, hypomethylated, methylation pattern for lymphoid neoplasm, methylation pattern for myeloid neoplasm, etc.
While the target regions disclosed with SEQ ID NOs indicate hypermethylated or hypomethylated, the manner in which they methylated are is not disclosed. First, the terms “hypermethylated” and “hypomethylated” are vaguely defined in para. 64 of the originally filed specification. The specification describes the elements in terms of a “high percentage” of CpG sites being unmethylated or methylated. The specification provides for sequences for target genomic regions, but then simply states that it is hypermethylated while also hypomethylated. There is no indication if sequencing data from cfDNA indicates a certain number of the CpG sites are methylated in a sequence corresponding to SEQ ID NO: 1, whether such a sequence is “hypermethylated” or “hypomethylated”. A partially methylated sequence is hypermethylated relative to the fully unmethylated sequence but hypomethylated relative to the fully methylated sequence. Similarly, there is no indication of whether a particular methylation pattern is relevant to being “hypermethylated” or “hypomethylated”. For example, do the first 3 CpG sites in a genomic region have to be methylated to be considered as a “hypermethylated” fragment.
In view of there being no description of what methylation status is relevant for the classifier to function, the claims are not adequately described.
The Remarks argue each of these tables is described as providing markers identified for particular cancers, following analysis of illustrative test results (p. 21).
The issue being raised by the Examiner is what methylation status of the disclosed target genomic regions in Table 1 are relevant to the identification of a HD versus another HD. There is no indication of whether a particular genomic region is to be hypermethylated, hypomethylated or have a particular methylation pattern to be used in the identification of a HD and which methylation status is relevant to a particular HD. The classifier functions by comparing known sequencing data regarding methylation to sequencing data obtained from a cfDNA sample. However, there is no indication of what information is required by the classifier regarding methylation status in order to be used and relied upon for detecting a particular HD based the various target genomic regions.
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 51, 53, 58-61, 68-69, 76-77, 85, 86 and 127-137 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.
Regarding claim 51, the claim broadly encompasses detecting the first HD with a trained classifier using information from 500 or more target genomic regions. The target genomic regions broadly encompass “differentially methylated” regions in “at least one HD relative to a different HD or relative to a non-HD cancer”.
The instant specification does not identify any combination of 500 target genomic regions that make up a functional “trained classifier” that is enabled for detecting cells of a particular HD. In regards to List 8, which is 22,456 target genomic regions, the instant specification analyzed random sets of 25% or 50% of the genomic regions of List 8, which equates to 5,614 and 11,228 target genomic regions, respectively. Sets of 25% from List 8 have ~11-fold more genes than that of a classifier trained on and analyzing sets of 500 target genomic regions. Stated differently, 500 target genomic regions represents only 2.2% of all the genes of List 8.
Even claim 77, which encompasses sets with 20% of List 8, results in only 4,491 target genomic regions being represented and these sets omit 17,964 target genomic regions of List 8. The even omit 1,123 target genomic regions (20%) of the sets of 25% of List 8 randomly tested in the specification.
The result is that the claims encompassing embodiments in which a vast majority of the disclosed target genomic regions that are informative for detecting an HD are omitted.
In view of this issue with the number of target genomic regions sequenced and analyzed by the “trained classifier” in the claimed panels, the art of Simon (Journal of Clinical Oncology. 2005. 23(29): 7332-7341) is relevant. Simon discusses issues associated with omitting informative genes (e.g., genes that are actually differentially expressed between classes), noting their omission has a greater deleterious effect on classification accuracy that does inclusion of noise genes (par. 7335, left column). As noted above, the claims are limited to a subset of disclosed target genomic regions that includes only 2.2% of List 8 target genomic regions. Thus, it is unpredictable whether or not the claimed sets of target genomic regions and their corresponding “trained classifiers” will work in the claimed methods because they omit numerous target genomic regions from the larger sets identified in the specification. The target genomic regions taught by the instant specification are all considered to be informative based on the instant specification.
The claims broadly encompass the use of at least 500 target genomic sequences from the recited “Lists” 1-8. For example, the claims encompass at least 500 target genomic sequences from List 8, which covers SEQ ID NOs: 34,881-57,336. A review of sequences from List 8 indicates that numerous sequences are duplicates of one another thus representing the same target genomic region. For example, SEQ ID NO: 42,207 and SEQ ID NO: 35,481 are identical and both map to chr2:9144127-9144172; however, SEQ ID NO: 42,207 is identified as being “hypo” and SEQ ID NO: 35,481 is identified as being “hyper”, in the Sequence Listing. SEQ ID NO: 36,081 and SEQ ID NO: 43,933 are identical and both map to chr3:160473309-160473405; however, SEQ ID NO: 36,081 is identified as being “hyper” and SEQ ID NO: 43,933 is identified as being “hypo”, in the Sequence Listing.
The instant specification does not describe in what context sequences are to be classified as “hyper” (understood to be “hypermethylated”) versus “hypo” (understood to be “hypomethylated”). The instant specification does not identify what distinguishes “hypermethylated” from “hypomethylated” and since the sequences are identical, it is unclear positions are or are not methylated within the target genomic regions. The specification does not identify whether such a sequence is relevant to detecting lymphoid neoplasm, multiple myeloma, myeloid neoplasm, etc. The instant specification does not identify which sequences of Table 1 or their methylation states that are relevant to detecting leukemia cells. The application does not adequately describe how to use the sequences disclosed in Table 1 for the detection of cells of a HD.
Quantity of Experimentation:
In order for one of ordinary skill in the art to practice the claimed method as broadly claimed, undue experimentation would be required. A number of parameters, including different types of HD and methylation panels, would have to be studied to establish that the analysis and consideration of any panel of 500 or more target genomic regions can be used to detect cells of an HD as claimed.
Conclusions:
Thus given the breadth of claims in an art whose nature is identified as unpredictable and the large quantity of research required to define these unpredictable variables is balanced only against the high skill level in the art, it is the position of the examiner that it would require undue experimentation for one of skill in the art to perform the method of the claim as broadly written.
Response to the traversal of the enablement rejections
The Remarks argue the amended claims are enabled (p. 22).
The Examiner’s position in view of the amended claims is detailed above.
The Remarks argue Simon (Journal of Clinical Oncology. 2005. 23(29): 7332-7341) is irrelevant for several reasons. First, the Remarks argue Simon relates to gene expression, not methylation of target genomic regions. Second, the Remarks argue Simon contains no disclosure at all concerning methylation, and thus provides no basis for extrapolating those conclusions to the present claims. Third, The Remarks argue even for gene expression, Simon states that "it is rarely necessary to measure expression for hundreds or thousands of genes in application of the classifier to subsequent cases" and instead postulates "developing genomic classifiers based on a limited number of genes". The Remarks argue here is no basis for drawing any negative conclusions about enablement for hundreds of markers defined by differential methylation (as in the present application) based on the disclosure in Simon concerning gene expression of "a limited number of genes". See p. 22. The Remarks further argue the present application provides examples of reduced lists of sequences useful in methods according to the presently claimed invention and reports results "indicat[ing] that a cancer determination can be made based solely on the methylation status of target genomic regions selected for the discrimination of hematological disorders or even individual hematological disorders," and that "performance of small panels of <500 kb indicates that panels of this size are sufficient for accurate cancer detection". See p. 22-23.
The arguments have been fully considered but are not persuasive. While smaller subsets of genomic regions are identified, there is no indication that panels as small as 500 genomic regions are enabled. Table 1 lists exemplary sets of target genomic regions. Lists 1 and 8 are related in that List 8 is a narrowed subset of List 1 and both are used to target “all” hematological disorders. List 8 represents 79.8% of List 1. There is no indication of a representative species of a subset of 500 target genomic regions that can be used to detect “all” hematological disorders.
List 5 is a narrowed subset of List 2 and both are used to target lymphoid neoplasms. List 5 represents 80.9% of list 2. There is no indication of a representative species of a subset of 500 target genomic regions that can be used to detect a lymphoid neoplasm.
List 6 is a narrowed subset of List 3 and both are used to target multiple myeloma. List 6 represents 93.5% of list 3. There is no indication of a representative species of a subset of 500 target genomic regions that can be used to detect a multiple myeloma.
List 7 is a narrowed subset of List 4 and both are used to target myeloid neoplasm. List 7 represents 93.8% of list 4. There is no indication of a representative species of a subset of 500 target genomic regions that can be used to detect a myeloid neoplasm.
In all the disclosed cases, a majority of the panels were utilized. While 75% of List 8 may not be included randomly, there is no indication that over 90% of the panel may be excluded. A significant number of genes still remain when only 25% of List 8 is randomly used.
The teachings of Simon are broadly applicable to creating panels or training classifiers on data. There is no evidence of why informative methylation biomarkers may be omitted from a panel and classifier, but not a gene expression biomarker. Both are biomarkers that are differentially occurring between to conditions, e.g., differentially methylated or differentially expressed.
Claim Rejections - 35 USC § 112
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 51, 53, 58-61, 68-69, 76-77, 86, 127-133 and 135-137 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.
Regarding claim 51, the claim recites the target genomic regions are differentially methylated. The claim is incomplete as no element in the claim collects methylation data that is needed for the “detecting” step.
The remainder of the examined claims depend from claim 51 and are also rejected for the above specified reasons, except for claims 85 and 134, which require the use of cfDNA samples converted based on methylation status.
Regarding claims 51, 77 and 78, the claim recites “a plurality of different oligonucleotides that collectively hybridize to at least 500 target genomic regions”. In the context of claims 77 and 78, the lists include duplicate target genomic regions. For example, List 8 includes SEQ ID NO: 42,207 and SEQ ID NO: 35,481, which are identical. It is unclear how one is to count these identical sequences as part of the at least 100 target genomic regions. If SEQ ID NO: 42,207 is included, is SEQ ID NO: 35,481 also included automatically? It is unclear how one includes SEQ ID NO: 35,481, but not SEQ ID NO: 42,207, and vice versa.
Furthermore, if SEQ ID NO: 42,207 and SEQ ID NO: 35,481 are to be differentially methylated, it is unclear if sequence does detected falls within a hypomethylated count, a hypermethylated count or a methylation pattern count because the sequences are identical.
Response to the traversal of the indefiniteness rejections
The Remarks argue the "a plurality of the at least 100 target genomic regions that are identified as hypermethylated or hypomethylated in the cfDNA fragments" has been deleted and the issue regarding this is moot (p. 24).
The claims remain rejected for the reasons provided above.
The Remarks argue the detecting step as amended is not incomplete (p. 25).
The claim remains rejected because the claim is incomplete. Methylation sequence data required for the “detecting” step is not an element of the claim.
The Remarks argue certain sequences having more than one SEQ ID NO entry in the sequence listing does not gives rise to any indefiniteness (p. 26). The Remarks further argue claim 51 does not recite a number of SEQ ID NOs, but instead a number of target genomic regions (p. 26).
The arguments have been fully considered but are not persuasive. The issue is not whether you can identify and count a particular sequence generically. The issue is how one is to count whether a sequence corresponding to a genomic region is hypermethylated, hypomethylated or has a methylation pattern that is relevant in the context of a particular HD. Using the disclosed target genomic regions, which are identified based on the sequences in the Sequence Listing, there is no information that is provided that distinguishes a hypomethylated genomic region from a hypermethylated genomic region because a single sequence is provided for both and no information regarding any methylation status of the CpG sites in the genomic region are provided.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 51, 53, 58, 59, 68, 69, 85, 86, 127, 128, 131, 132, 133, 134 and 135 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mazloom (US 2018/0032671) in view of Zhang (US 2018/0341745).
The following are new rejections necessitated by the amendments.
Regarding claims 51, 53, 127, 128 and 132, Mazloom teaches detection of different types of cancer compared to healthy individuals (para 374-376), including leukemia (para. 100 and 376) and multiple myeloma (para. 376).
Mazloom teaches a method of capturing DNA molecules with bait oligonucleotides and sequencing (para. 124 and 136-139). Mazloom teaches the bait can hybridize to methylated target genomic regions of size of 10 Kb, 100 KB, 500KB, 1000KB, 5000 Kb or 10000kb in length wherein the fragments include sets of 1,000 or more sampled regions (para 54 and 349). Therefore, Mazloom teaches measuring multiple regions of methylated target genomic regions as a training vector.
Mazloom further teaches the regions include features including fraction of methylated nucleotides or methylation state (para. 182) or aberrant methylation (para. 291) or distinct methylation sites or distinct methylation patterns (para. 349). Because Mazloom deals with fractions of nucleotides and methylation states or patterns, the DNA molecules captured have multiple CpG sites.
Mazloom teaches applying a trained classifiers (para 194) to detect a disorder, such as leukemia or multiple myeloma.
Given the broad scope of generic “trained classifiers” encompassed by the claims and the generic target genomic regions, Mazloom renders obvious this aspect of the claim. The claims essentially encompass using any useful methylation sites selected based on a generic