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 .
Restriction/Election
Applicant’s election without traverse of Group I, drawn to methods of identifying regulatory T cell markers and corresponding to claims 24-32 in the reply filed 02/11/2026 is acknowledged.
Claim Status
The amendment filed 02/11/2026 is acknowledged. Claims 24-41 are pending. Claims 33-41 are withdrawn for being directed to a non-elected invention.
Claims 24-32 are under examination.
Specification
The disclosure is objected to because it contains an embedded hyperlink and/or other form of browser-executable code. Applicant is required to delete the embedded hyperlink and/or other form of browser-executable code; references to websites should be limited to the top-level domain name without any prefix such as http:// or other browser-executable code. See MPEP § 608.01.
The use of the terms LiberaseTM and DynaBeadsTM, which are trade names or a marks used in commerce, has been noted in this application. The terms should be accompanied by the generic terminology; furthermore the term should be capitalized wherever it appears or, where appropriate, include a proper symbol indicating use in commerce such as ™, SM , or ® following the term.
Although the use of trade names and marks used in commerce (i.e., trademarks, service marks, certification marks, and collective marks) are permissible in patent applications, the proprietary nature of the marks should be respected and every effort made to prevent their use in any manner which might adversely affect their validity as commercial marks.
Claim Rejections - 35 USC § 112(b)
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 24-32 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 24, the term “conventional T cell” can read on both CD4+ T cells and CD8+ T cells. The specification teaches that Tconv “may be” defined as CD45+CD4+CD25loCD126lo/hi, but does not provide a definitive definition (Specification, Pg. 13). In the instant case, the claim requires that the Tregs and Tconvs are prepared in a mixture of similar proportions. In order for the metes and bounds of this active step to be clear, the term “Tconv” should be appropriately defined. As an example, the claim can incorporate the CD45+CD4+CD25hiCD126lo Treg phenotype and CD45+CD4+CD25loCD126lo/hi Tconv phenotype as disclosed in the specification or a CD4+ FACs sorting step as disclosed in the specification can be added (Pg. 14, Lines 29-31). All dependent claims are rejected for not providing limitations that mediate the indefiniteness rejection of claim 24.
Regarding claim 28, the phrase "in particular" renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
Regarding claim 31, the meaning of the term “for therapeutic purpose” is unclear and the meaning of the phrase is not defined within the specification. For clarity, the phrase may be changed at the applicant’s discretion to mirror the language of step 8 to read: “ranking of tumor-specific Treg markers as candidate therapeutic targets”.
Claim Rejections - 35 USC § 103
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.
Claims 24-32 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang (Nature. 2018 Dec;564(7735):268-272, cited in IDS filed 08/19/2022) in view of Hindley (Cancer Res. 2011 Feb 1;71(3):736-46) as evidenced by Coussens (Nature. 2002 Dec 19-26;420(6917):860-7) .
Regarding claim 24, pertaining to a method of identification of functional disease-specific regulatory T cell makers, Zhang teaches the following instantly claimed steps:
Preparing a mixture of isolated regulatory T (Treg) cells and conventional T (Tconv) cells in similar proportions from at least a patient diseased-tissue sample and a patient peripheral blood sample – Zhang discloses the data of the study were obtained from blood, tumor and normal tissue specimens from colorectal cancer patients (Study design in Extended Fig. 1a)
Performing single-cell gene expression profiling combined with T cell receptor (TCR) profiling on each mixture of isolated Treg and Tconv cells from at least diseased-tissue and peripheral blood – Zhang discloses isolated T cells from the patient specimens underwent single cell gene expression sequencing and single cell TCR profiling (Study design in Extended Fig. 1a). Zhang claim 1a overlays the two sets of data to show individual cells within each cluster that express clonally expanded TCRs.
Identifying clusters of Treg cells and Tconv cells, wherein the clusters comprise differentially expressed genes or gene signatures between each other – Zhang Fig. 1a shows three Treg populations that clustered separately from each other and separately from the Tconvs based on differential gene expression profiles.
Determining at least one cluster of functional disease-specific Treg cells among the identified clusters of Treg cells, wherein the at least one cluster comprises (i) a higher proportion of Treg cells in the diseased-tissue than in the peripheral blood;(ii) a higher proportion of Treg cells with clonally expanded TCR specificities in the diseased-tissue; and(iii) a higher proportion of Treg cells with a transcriptomic signature of TCR triggering, cell activation and expansion in the diseased-tissue – Zhang Fig. 1a and 1b show 3 different Treg populations whose differential gene expression correlates with the tissue specimen from which they were isolated; Zhang teaches the three FOXP3+ Treg cell clusters, CD4_C10-FOXP3, CD4_C11-IL10 and CD4_C12-CTLA4, were enriched in blood, normal mucosa and tumours, respectively (Pg. 269, Left column, Lines 6-8).
Identifying genes that are differentially expressed in the cluster of functional disease-specific Treg cells in comparison with all the other identified clusters of Treg and Tconv cells – Zhang has identified the Treg cluster CD4_CD12-CTLA4 (T.Treg) which is enriched in the tumor cells and identifies a gene signature associated with the tumor Treg cluster compared to the non-tumor Treg cell populations and Tconv populations (Extended Data Fig. 4b, see far right column of heatmap and Extended Data Fig. 5d).
Regarding claim 25, wherein the patient diseased tissue is a patient tumor sample, the specimens from Zhang’s analysis were obtained from colorectal cancer patient tumor tissue, normal tissue, and peripheral blood (Extended Data Fig. 1).
Regarding claim 27, wherein the combined single-cell gene expression profiling and T cell receptor (TCR) profiling in step (b) is performed by single-cell RNA sequencing method, Zhang discloses isolated T cells of from the patient specimens underwent both single cell gene expression sequencing and single cell TCR profiling (Study design in Extended Fig. 1a).
Regarding claim 28, wherein the at least one cluster of functional disease-specific Treg cells comprises a higher proportion of Treg cells overexpressing one or more of the disclosed genes, this limitation is an intended result of the screening method and does not add to or modify the active method steps of the claimed method. To this end, however, Zhang does show the tumor Treg population is enriched for TNFRSF9 (4-1BB) expression (Extended Data Fig. 4 and 5).
Regarding claims 29 and 30, wherein the disease is selected from the disclosed lists, Zhang also analyzed a T cell scRNA-seq data set for non-small cell lung cancer (NSCLC) and processed the data using the same pipeline as the dataset from colorectal cancer patients to allow for comparison (Pg. 275, Left column, Analysis of combined CRC, HCC, and NSCLC and Extended Data Fig. 10). The cancers disclosed in Zhang reasonably read on chronic inflammatory disease (claim 30) as evidenced by Coussens who teaches that not only does cancer often arise as a result of chronic inflammation and infection (i.e. colon carcinogenesis, Pg. 6 Cancers associated with chronic inflammation), cancer also drives chronic inflammation by producing cytokines and chemokines that attract leukocytes (Pg. 4, Inflammatory cell component of tumours).
Regarding claims 31 and 32, pertaining to a method of identifying and ranking tumor specific Treg markers (claim 31), wherein the Treg markers are transmembrane proteins with an extracellular domain (claim 32), Zhang teaches bioinformatic methods that anticipate the ranking method of the instant claims. The instant claims provide steps wherein proteins are ranked based on their expression level on tumor Tregs. The claimed steps prioritize markers with lower expression in normal tissues (Step 2), non-Treg PBMCs (Step 4) and non-Treg tumor cells (Step 5) and prioritize markers with higher expression in tumoral tissues (Step 3), the highest fold change difference between tumor Tregs compared to normal tissue and between Tregs and Tconvs. Zhang’s clustering methods also identify genes that differentiate tumor T regs from cells in normal tissue, blood and from non-Treg tumor cells based on their differential expression; this is seen for example, in Extended Data Fig. 5. Extended Data Fig. 5c shows cells clustering based on gene expression. The CD4_C12 T Treg cluster was formed based on gene expression that differentiated this group of cells from cells in the blood, normmal tissues and from other tumor cells (far right panel, copper colored cluster). In further anticipation of the claimed method, Extended Data 5d provides a list of genes that are representative of the tumor Treg population, including membrane proteins CCR8, CTLA4 and TNFRSF18, which were also identified through the instant claimed methods (Specification Table 1).
The disclosure of Zhang does not teach: the cell mixture comprises Tregs and Tconv in a similar proportion.
These deficiencies are taught by Hindley.
The disclosure of Hindley is directed to investigating the mechanism of intra-tumoral accumulation of Tregs, as enrichment of Tregs is frequently observed in murine and human carcinomas and can limit anti-tumor responses and promote tumor progression (see Abstract).
Regarding claims 24 and 26, wherein the cell mixture of Tregs and Tconv are in a similar proportion (claim 1) and about 50% Treg and 50% Tconv (claim 26), Hindley teaches isolation of Treg and Tconv cells in a MCA-induced fibrosarcoma model that is characterized by enriched Foxp3+ cell accounting for 40-50% CD4+T cells in the tumor. Hindley confirmed significant accumulation of Tregs in the study (Pg. 4, Enrichment of CD4+FoxP3+ T cells in tumor and draining lymph node).
It would have been prima facie obvious to one having ordinary skill in the art at the time of filing to modify the method of Zhang to compare Tregs and Tconv at a similar proportion as taught by Hindley. One would have been motivated to do so because Tregs are present in peripheral blood and tissues at a lower percentage than conventional T cells and are underrepresented in T cell datasets. Hindley specifically chose a model with upregulated Treg population to overcome this limitation. In cancer models where Tregs are expressed in lower proportions, one could be motivated by the teachings of Hindley to alter the ratios of the cells input into the sequencing steps by providing an amount of Treg equal to the amount of Tconvs. There would be an expectation of success in making this modification to Zhang because altering the ratio or Treg/Tconv in the sequenced sample would not affect the subsequent single cell RNA-seq and screening steps.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAROL ANN CHASE whose telephone number is (571)270-0934. The examiner can normally be reached Monday-Friday 9:00am-6:00pm.
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/CAROL ANN CHASE/ Examiner, Art Unit 1646
/HONG SANG/ Primary Examiner, Art Unit 1646