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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Status of Claims
This communication is in response to the Application Filed on 01/16/2024.
Claims 16-34 are pending in this application.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 01/16/2024 and 04/16/2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Drawings
The drawings are objected to because the unlabeled rectangular box(es) shown in the drawings should be provided with descriptive text labels. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because of the following informalities:
In page 6, par.2, line 3, “call” should be “cell”
In page 8, par. 3, line 7, “last” should be “least”
In page 13, par. 3, line 7, “call” should be “cell”
In page 22, par. 2, line 1, “10’000” should be “10,000”
In page 22, par. 2, line 14, “immunohistochemestry” should be “immunohistochemistry”
Appropriate correction is required.
Claim Objections
Claims 1, 7, and 28-29 are objected to because of the following informalities:
In claim 1, please change the first instance of “IHC” to “immunohistochemistry (IHC)” as abbreviations change in meaning over time and it is the first instance of this abbreviation.
In claim 17, “call” should be “cell”.
Claim 30 is objected to under 37 CFR 1.75 as being a substantial duplicate of claim 28 (despite slight difference in wording).
Claim 31 is objected to under 37 CFR 1.75 as being a substantial duplicate of claim 29 (despite slight difference in wording).
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.
Such claim limitation(s) is/are:
“second deep learning system” in claim 20
“first deep learning system” in claim 22
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
Claim 20: ‘second deep learning system’ corresponds to “a second deep convolutional network (DeepLab3+),” Applicant Specification Pg. 16 line 15.
Claim 22: ‘first deep learning system’ corresponds to “detection system consisted of a convolutional neural network (U-Net),” Applicant Specification Pg. 16, lines 5-6.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 19 and 21 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 19 recites “wherein the second automatic image data analysis step further comprises applying a second deep learning system comprising a convolutional neural network.” It is unclear what “applying a second deep learning system comprising a convolutional neural network” is referring to. Appropriate correction is required. For purposes of examination, Examiner is interpreting “applying a second deep learning system comprising a convolutional neural network” as being applied for identification of image regions comprising non-malignant cells, and excluding the image regions comprising the non-malignant cells from further analysis, as stated in Claim 16.
Claim 22 recites “wherein the first automatic image data analysis step further comprises applying a first deep learning system comprising a convolutional neural network.” It is unclear what “applying a first deep learning system comprising a convolutional neural network” is referring to. Appropriate correction is required. For purposes of examination, Examiner is interpreting “applying a first deep learning system comprising a convolutional neural network” as being applied to converting the multiplex fluorescence image data to segmented image data, as stated in Claim 16.
Claims 20 and 22-23 are rejected for the same reason, due to their dependency.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 16-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Shipitsin et al. (WO 2014144657 A2, hereafter, "Shipitsin").
Regarding claim 16, Shipitsin discloses a method for measuring a prognostic marker in prostate cancer or in breast cancer, the method comprising (See Shipitsin, Pg. 23, lines 4-5, methods for predicting prognosis of cancer (e.g., prostate cancer) in a patient; Pg. 51, lines 24-25, measuring the expression (e.g., protein expression) or activity levels of the biomarkers in a cancerous tissue sample; Pg. 110, lines 16-17, prognostic markers, PTEN, SMAD4, CCNDl and SPPl, can predict lethal outcome of human prostate cancer):
obtaining a tissue section of one of prostate tissue or breast tissue (See Shipitsin, Pg. 68, lines 17-18, Tissue samples used in the methods of the invention may be tumor samples (e.g., prostate tumor samples) obtained by biopsy);
multiplex fluorescence IHC-staining of the tissue section (See Shipitsin, Pg. 69, lines 25-25, Exemplary methods for determining the levels at the protein level include, without limitation, immunoassays such as immunohistochemistry assays (IHC); Pg. 70, lines 8-10, In an IHC assay, detectably-labeled antibodies to the various biomarkers can be used to stain a prostate tissue sample and the levels of binding can be indicated by, e.g., fluorescence or luminescent emission) using a first marker (See Shipitsin, Pg. 71, lines 7-10; cytokeratin 8 (CK8 or KRT8) and cytokeratin 18 (CK18 or KRT18)) for labelling epithelial cells (See Shipitsin, Pg. 71, lines 7-10; expressing epithelial markers such as cytokeratin 8 (CK8 or KRT8) and cytokeratin 18 (CK18 or KRT18)), a second marker (See Shipitsin, Pg. 71, lines 10-11, cytokeratin 5 (CK5 or KRT5)) for labelling basal cells and at least one prognostic marker (See Shipitsin, Pg. 71, lines 10-11, expressing prostate basal markers such as cytokeratin 5 (CK5 or KRT5));
obtaining multiplex fluorescence image data (See Shipitsin, Pg. 99, lines 9-10, Two Vectra Intelligent Slide Analysis Systems (PerkinElmer) were used for quantitative multiplex immunofluorescence (QMIF) image acquisition);
performing a first automatic image data analysis step (See Shipitsin, Pg. 100, lines 18-19, define fluorescent cut-offs for tissue segmentation in each individual tissue sample in our image analysis algorithm) comprising converting the multiplex fluorescence image data to segmented image data, wherein the segmented image data is segmented according to cell types including at least epithelial cells and basal cells (See Shipitsin, Pg. 100, line 21, tissue samples were segmented using the fluorescent epithelial and basal cell markers);
performing a second automatic image data analysis step (See Shipitsin, Pg. 100, lines 24-26, Fields with artifact staining, insufficient epithelial tissue, and out of focus were removed by a rigorous multi-parameter quality control algorithm) comprising identification of image regions comprising non-malignant cells, and excluding the image regions comprising the non-malignant cells from further analysis (See Shipitsin, Pg. 124, lines 27-29, In order to quantitatively measure biomarkers in tumor epithelium only, we needed to achieve "tissue segmentation", distinguishing tumor from benign areass);
and determining a quantitative parameter of the at least one prognostic marker for epithelial cells in an image region not excluded in the second automatic image data analysis step (See Shipitsin, Pg. 125, lines 6-7, quantitative biomarker values were extracted only from cancer epithelium).
Regarding claim 17, Shipitsin discloses the method of claim 16, the second automatic image data analysis step further comprises determining distances between the epithelial cells and the basal cells, wherein epithelial cells being closer than a predefined distance to a nearest basal call are identified as non-malignant (See Shipitsin, Pg. 123, lines 3-7, Benign prostate glands contain basal cells and luminal cells, whereas prostate cancer glands lack basal cells and have smaller luminal profiles. Therefore, individual gland regions were classified as malignant or benign based on the relational features between basal cells and adjacent epithelial structures combined with object-related features, such as gland size).
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.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Shipitsin et al. (WO2 014144657 A2), hereafter, "Shipitsin") in view of Vidi (Three-Dimensional Culture of Human Breast Epithelial Cells: The How and the Why, 2012, hereafter, “Vidi”).
Regarding claim 18, which claim 17 is incorporated, Shipitsin fails to disclose wherein the predefined distance is in a range from 5 µm to 60 µm.
Vidi teaches wherein the predefined distance is in a range from 5 µm to 60 µm (See Vidi, Pg. 198, lines 10-15, In the presence of the appropriate substratum (i.e., BM components and a specific mechanical environment) (20), S1 cells differentiate into basoapically polarized acinus-like structures of approximately 30 µm in diameter containing 25–35 cells (36) (see Fig. 2). Basoapical polarity is a critical feature of normal breast epithelia. Examiner considers 30 µm to cover this claim, as it falls within the given range and a specific value was not given).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference wherein the predefined distance is in a range from 5 µm to 60 µm based on the method of Vidi’s reference. The suggestion/motivation would have been to provide physiologically relevant models to study normal development and disease as suggested by Vidi in Pg. 193, lines 7-8.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Vidi with Shipitsin to obtain the invention as specified in claim 18.
Claims 19-23 are rejected under 35 U.S.C. 103 as being unpatentable over Shipitsin et al. (WO 2014144657 A2), hereafter, "Shipitsin") in view of Bulten et al. (Epithelium segmentation using deep learning in H&E stained prostate specimens with immunohistochemistry as reference standard, 2019, hereafter, “Bulten”).
Regarding claim 19, which claim 16 is incorporated, Shipitsin discloses wherein the second automatic image data analysis step [further comprises applying a second deep learning system comprising a convolutional neural network] (See Shipitsin, Pg. 100, lines 24-26, Fields with artifact staining, insufficient epithelial tissue, and out of focus were removed by a rigorous multi-parameter quality control algorithm).
However, Shipitsin fails to disclose applying a second deep learning system comprising a convolutional neural network.
Bulten teaches applying a second deep learning system comprising a convolutional neural network (See Bulten, Pg. 1, last paragraph, line 6, computer-aided, diagnostic tools based on deep learning and convolutional neural networks have shown promise in improving the accuracy and efficiency of histopathological diagnosis; Pg. 2, third full paragraph, lines 1-3, trained a convolutional network to segment epithelium in immunohistochemically (IHC) stained tissue sections applying an epithelial marker; Pg. 6, par. 6, line 4, trained a six-level-deep U-Net).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference to applying a second deep learning system comprising a convolutional neural network based on the method of Bulten’s reference. The suggestion/motivation would have been for computer-aided, diagnostic tools based on deep learning and convolutional neural networks which have shown promise in improving the accuracy and efficiency of histopathological diagnosis as suggested by Bulten in Pg. 1-2, par. 4, lines 6-7.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Bulten with Shipitsin to obtain the invention as specified in claim 19.
Regarding claim 20, which claim 19 is incorporated, Shipitsin discloses [wherein the second deep learning system] is configured to classify data according to one or more classes, wherein the classes are selected from a group consisting of benign gland, tumor gland, autofluorescence, stroma, and background (See Shipitsin, Fig 27D; Pg. 41, lines 29-31 and Pg 42 lines 1-4, Moving through parts 1-6, from the composite image (1), first total epithelial regions were identified (2), followed by nuclear areas (3). The epithelial regions were further segmented into tumor (which was visualized in red), benign (which was visualized in green), and undetermined (which was visualized in yellow) (4). Gray color denoted non-epithelial regions, e.g. stroma and vessels (4). Finally, biomarkers were quantified from tumor epithelium areas only, which were outlined in red (5 and 6)).
However, Shipitsin fails to disclose the second deep learning system.
Bulten teaches the second deep learning system (See Bulten, Pg. 1, last paragraph, line 6, computer-aided, diagnostic tools based on deep learning and convolutional neural networks have shown promise in improving the accuracy and efficiency of histopathological diagnosis; Pg. 2, third full paragraph, lines 1-3, trained a convolutional network to segment epithelium in immunohistochemically (IHC) stained tissue sections applying an epithelial marker).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference to applying a second deep learning system comprising a convolutional neural network based on the method of Bulten’s reference. The suggestion/motivation would have been for computer-aided, diagnostic tools based on deep learning and convolutional neural networks which have shown promise in improving the accuracy and efficiency of histopathological diagnosis as suggested by Bulten in Pg. 1-2, par. 4, lines 6-7.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Bulten with Shipitsin to obtain the invention as specified in claim 20.
Regarding claim 21, which claim 16 is incorporated, Shipitsin discloses wherein the first automatic image data analysis step [further comprises applying a first deep learning system comprising a convolutional neural network] (See Shipitsin, Pg. 100, lines 18-19, define fluorescent cut-offs for tissue segmentation in each individual tissue sample in our image analysis algorithm).
However, Shipitsin fails to disclose applying a first deep learning system comprising a convolutional neural network.
Bulten teaches applying a first deep learning system comprising a convolutional neural network (See Bulten, Pg. 2, par. 6, lines 1-3, trained a convolutional network to segment epithelium in immunohistochemically (IHC) stained tissue sections applying an epithelial marker; Pg. 6, par. 6, line 4, trained a six-level-deep U-Net).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference to applying a first deep learning system comprising a convolutional neural network based on the method of Bulten’s reference. The suggestion/motivation would have been to improve the accuracy and efficiency of histopathological diagnosis as suggested by Bulten in Pg. 1-2, par. 4, lines 6-7.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Bulten with Shipitsin to obtain the invention as specified in claim 21.
Regarding claim 22, which claim 21 is incorporated, Shipitsin and Bulten teach wherein the first deep learning system carries out the segmentation according to cell types without an operator having to set a threshold value for an intensity of one of the markers (See Shipitsin, Pg. 122, lines 30-31 and Pg. 123, lines 1-2, Autoadaptive thresholding was used to define fluorescent intensity cut-offs for tissue segmentation in each individual tissue sample).
Regarding claim 23, which claim 21 is incorporated, Shipitsin and Bulten teach wherein the first deep learning system based on the multiplex fluorescence image data defines an individual threshold value for an intensity of at least one of the markers (See Shipitsin, Pg. 100, lines 18-19, Built-in auto-adaptive thresholding was used to define fluorescent cut-offs for tissue segmentation in each individual tissue sample in our image analysis algorithm; Pg. 100, lines 22-24, Tissue samples were segmented using DAPI along with fluorescent epithelial and basal cell markers to allow classification as epithelial cells, basal cells and stroma).
Claims 25-26 are rejected under 35 U.S.C. 103 as being unpatentable over Shipitsin et al. (WO 2014144657 A2), hereafter, "Shipitsin") in view of Desmeules et al. (Comparison of digital image analysis and visual scoring of KI-67 in prostate cancer prognosis after prostatectomy, 2015, hereafter, “Desmeules”).
Regarding claim 25, which claim 16 is incorporated, Shipitsin fails to disclose wherein the at least one prognostic marker includes antibodies directed against proliferating cells.
Desmeules teaches wherein the at least one prognostic marker includes antibodies directed against proliferating cells (See Desmeules, Pg. 5, Right col., lines 1-4, Uncontrolled proliferation is a hallmark of malignancy and the measurement of Ki-67 antigen by immunohisto-chemistry is the most widely performed assessment of the proliferative potential of tumors).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference teaches wherein the at least one prognostic marker includes antibodies directed against proliferating cells based on the method of Desmeules’s reference. The suggestion/motivation would have been to support the role of Ki-67 proliferative index as an important prognostic factor of BCR and DPCa in prostate cancer post as suggested by Desmeules in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Desmeules with Shipitsin to obtain the invention as specified in claim 25.
Regarding claim 26, which claim 16 is incorporated, Shipitsin fails to disclose wherein the at least one prognostic marker includes Ki67 antibodies.
Desmeules teaches wherein the at least one prognostic marker includes Ki67 antibodies (See Desmeules, Pg. 9, Left col., lines 3-5 left, Ki-67, a proliferating marker associated with risk of BCR and DPCa in prostate cancer patients).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference teaches wherein the at least one prognostic marker includes antibodies directed against proliferating cells based on the method of Desmeules’s reference. The suggestion/motivation would have been to support the role of Ki-67 proliferative index as an important prognostic factor of BCR and DPCa in prostate cancer post as suggested by Desmeules in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Desmeules with Shipitsin to obtain the invention as specified in claim 26.
Claims 27-31 and 33-34 are rejected under 35 U.S.C. 103 as being unpatentable over Shipitsin et al. (WO 2014144657 A2), hereafter, "Shipitsin") in view of Shipitsin et al. (Automated quantitative multiplex immunofluorescence in situ imaging identifies phospho-S6 and phospho-PRAS40 as predictive protein biomarkers for prostate cancer lethality, 2014, hereafter, “Shipitsin 2”).
Regarding claim 27, where claim 16 is incorporated, Shipitsin fails to disclose wherein at least two different prognostic markers are applied.
Shipitsin 2 teaches wherein at least two different prognostic markers are applied (See Shipitsin 2, Fig. 4A-B; Pg. 6, Left col., Line 18, using the same 4 markers reported to predict lethal outcome; Pg. 7, Right col., lines 13-15, identifies pPRAS40 and pS6 as prognostic markers for prostate cancer. Examiner considers the same 4 markers with the addition of pPRAS40 and pS6 as a total of 6 markers).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference teaches wherein at least two different prognostic markers are applied based on the method of Shipitsin 2’s reference. The suggestion/motivation would have been to reproducibly and simultaneously quantify and assess multiple protein levels and functional activities on intact tissue specimens as suggested by Shipitsin 2 in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Shipitsin 2 with Shipitsin to obtain the invention as specified in claim 27.
Regarding claim 28, where claim 16 is incorporated, Shipitsin fails to disclose wherein at least three different prognostic markers are applied.
Shipitsin 2 teaches wherein at least three different prognostic markers are applied (See Shipitsin 2, Fig. 4A-B; Pg. 6, Left col., Line 18, using the same 4 markers reported to predict lethal outcome; Pg. 7, Right col., lines 13-15, identifies pPRAS40 and pS6 as prognostic markers for prostate cancer. Examiner considers the same 4 markers with the addition of pPRAS40 and pS6 as a total of 6 markers).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference teaches wherein at least three different prognostic markers are applied based on the method of Shipitsin 2’s reference. The suggestion/motivation would have been to reproducibly and simultaneously quantify and assess multiple protein levels and functional activities on intact tissue specimens as suggested by Shipitsin 2 in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Shipitsin 2 with Shipitsin to obtain the invention as specified in claim 28.
Regarding claim 29, where claim 16 is incorporated, Shipitsin fails to disclose wherein at least five different prognostic markers are applied.
Shipitsin 2 teaches wherein at least five different prognostic markers are applied (See Shipitsin 2, Fig. 4A-B; Pg. 6, Left col., Line 18, using the same 4 markers reported to predict lethal outcome; Pg. 7, Right col., lines 13-15, identifies pPRAS40 and pS6 as prognostic markers for prostate cancer. Examiner considers the same 4 markers with the addition of pPRAS40 and pS6 as a total of 6 markers).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference teaches wherein at least five different prognostic markers are applied based on the method of Shipitsin 2’s reference. The suggestion/motivation would have been to reproducibly and simultaneously quantify and assess multiple protein levels and functional activities on intact tissue specimens as suggested by Shipitsin 2 in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Shipitsin 2 with Shipitsin to obtain the invention as specified in claim 29.
Regarding claim 30, where claim 16 is incorporated, Shipitsin fails to disclose wherein at least three prognostic markers are applied.
Shipitsin 2 teaches wherein at least three prognostic markers are applied (See Shipitsin 2, Fig. 4A-B; Pg. 6, Left col., Line 18, using the same 4 markers reported to predict lethal outcome; Pg. 7, Right col., lines 13-15, identifies pPRAS40 and pS6 as prognostic markers for prostate cancer. Examiner considers the same 4 markers with the addition of pPRAS40 and pS6 as a total of 6 markers).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference teaches wherein at least three prognostic markers are applied based on the method of Shipitsin 2’s reference. The suggestion/motivation would have been to reproducibly and simultaneously quantify and assess multiple protein levels and functional activities on intact tissue specimens as suggested by Shipitsin 2 in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Shipitsin 2 with Shipitsin to obtain the invention as specified in claim 30.
Regarding claim 31, where claim 16 is incorporated, Shipitsin fails to disclose wherein at least five prognostic markers are applied.
Shipitsin 2 teaches wherein at least five prognostic markers are applied (See Shipitsin 2, Fig. 4A-B; Pg. 6, Left col., Line 18, using the same 4 markers reported to predict lethal outcome; Pg. 7, Right col., lines 13-15, identifies pPRAS40 and pS6 as prognostic markers for prostate cancer. Examiner considers the same 4 markers with the addition of pPRAS40 and pS6 as a total of 6 markers).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference teaches wherein at least five prognostic markers are applied based on the method of Shipitsin 2’s reference. The suggestion/motivation would have been to reproducibly and simultaneously quantify and assess multiple protein levels and functional activities on intact tissue specimens as suggested by Shipitsin 2 in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Shipitsin 2 with Shipitsin to obtain the invention as specified in claim 31.
Regarding claim 33, where claim 16 is incorporated, Shipitsin fails to disclose wherein the second marker comprises a p63 antibody.
Shipitsin 2 teaches wherein the second marker comprises a p63 antibody (See Shipitsin 2, Pg. 71, line 27, p63 antibody for basal cells).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference wherein the second marker comprises a p63 antibody based on the method of Shipitsin 2’s reference. The suggestion/motivation would have been to reproducibly and simultaneously quantify and assess multiple protein levels and functional activities on intact tissue specimens as suggested by Shipitsin 2 in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Shipitsin 2 with Shipitsin to obtain the invention as specified in claim 33.
Regarding claim 34, where claim 16 is incorporated, Shipitsin fails to disclose wherein the multiplex fluorescence IHC-staining comprises diamidino-2-phenylindole (DAPI) staining.
Shipitsin 2 teaches wherein the multiplex fluorescence IHC-staining comprises diamidino-2-phenylindole (DAPI) staining (See Shipitsin 2, Pg. 71, lines 14-15, a prostate tissue sample may be stained with nuclear-specific fluorescent dyes, such as DAPI).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference wherein the multiplex fluorescence IHC-staining comprises diamidino-2-phenylindole (DAPI) staining based on the method of Shipitsin 2’s reference. The suggestion/motivation would have been to reproducibly and simultaneously quantify and assess multiple protein levels and functional activities on intact tissue specimens as suggested by Shipitsin 2 in the Abstract.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Shipitsin 2 with Shipitsin to obtain the invention as specified in claim 34.
Claim 32 is rejected under 35 U.S.C. 103 as being unpatentable over Shipitsin et al. (WO 2014144657 A2), hereafter, "Shipitsin") in view of Wang et al. (WO2004093646 A2, hereafter, “Wang”).
Regarding claim 32, where claim 16 is incorporated, Shipitsin fails to disclose wherein the first marker comprises a pan cytokeratin (CKpan) antibody, in particular AEI/AE3 antibodies.
Wang teaches wherein the first marker comprises a pan cytokeratin (CKpan) antibody, in particular AEI/AE3 antibodies (See Wang, Pg. 49, lines 9-10, antibodies directed towards pan-cytokeratin (AE1/AE3; DAKO)).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Shipitsin’s reference wherein the first marker comprises a pan cytokeratin (CKpan) antibody, in particular AEI/AE3 antibodies based on the method of Wang’s reference. The suggestion/motivation would have been to provide specific methods and reagents for the diagnosis, staging, prognosis, monitoring, and treatment of diseases associated with cancer, or to indicate a predisposition to such for preventative measures as suggested by Wang in Pg. 3, par. 3, lines 6-10.
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Wang with Shipitsin to obtain the invention as specified in claim 32.
Allowable Subject Matter
Claim 24 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim 24 contains subject matter that is not disclosed or made obvious in the cited art.
Zagorchev (WO 2013179188 A1) discloses a method for quantitative evaluation of image segmentation. In Pg. 4, lines 17-19, “The ground truth data contains information about the intensity values at the boundary of each structure, which may be used to derive an image metric showing the quality of segmentation.”
In regard to claim 24, when considering claim 24 as a whole, prior art of record fails to disclose or render obvious, alone or in combination:
“The method of claim 16, wherein the quantitative parameter of the at least one prognostic marker is a ratio of the number of epithelial cells exhibiting a high fluorescence intensity of the at least one prognostic marker compared to a number of epithelial cells exhibiting a low fluorescence intensity of the at least one prognostic marker.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kasper (US 20050112706 A1) discloses a prognostic method for characterizing biopsy samples, biological samples, cells, and tissues and their respective activity of the androgen receptor in the human prostate epithelial cells to identify disease markers or determine a treatment regimen.
Dittamore (US 10527624 B2) discloses a method for detecting castration-resistant prostate cancer through immunofluorescence staining and characterization of nucleated cells as well as detecting measurable features in of biomarkers in a panel.
Gillies (US 20160260211 A1) discloses a method of diagnosing tumors by performing a quantitative analysis of a radiological image to identify a region of interest in which to classify the tumor object.
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/JASMIN MARCELINO HERNANDEZ/Examiner, Art Unit 2676
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
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