1. A method of treating breast cancer comprising
experimentally obtaining a dataset associated with a sample derived from a patient diagnosed with cancer, wherein the dataset comprises:
expression data for at least one marker selected from the group consisting of FLJ10517, HCAP-G, CDKN3, STK6, FOXM1, FLJ10540, TNFRSF6B, HBP17, C1QDC1, TUBG1, FLJ10036, RRM2, ACTB, ACTN1, EPHA2, TRIP13, CKS2, VRK1, DUSP4, EIF4A1, SERPINE2, and ODC1 andoptionally at least one clinical factor;
determining a predictive score from the dataset using an interpretation function, wherein
the predictive score is predictive of the response to the cancer treatment; and
administering a therapeutically effective amount of the cancer treatment to the patient who is predicted to respond to the cancer treatment.
2-7. (canceled)
8. The method of claim 1, wherein the determining is determined by a computer processor.
9. The method of claim 1, wherein the dataset further comprises the expression data and the at least one clinical factor.
10. The method of claim 9, wherein the at least one clinical factor term is selected from the group consisting of age, gender, neutrophil count, ethnicity, race, disease duration, diastolic blood pressure, systolic blood pressure, a family history parameter, a medical history parameter, a medical symptom parameter, height, weight, a body-mass index, smokernon-smoker status, ER status, HER2 status, tumor size, tumor grade, luminal A characterization, luminal B characterization, basal-like, and normal-like.
11. The method of claim 1, wherein the predictive score is compared to a score derived from a sample from a patient with cancer that was known to have responded or not responded to chemotherapy,
wherein a sample whose score matches the predetermined predictive of sample derived from a patient that responded to treatment the patient diagnosed with cancer is predicted to respond to the cancer treatment, or
wherein a sample whose score matches the predetermined predictive of sample derived from a patient that did not respond to treatment the patient diagnosed with cancer is predicted to not to respond to the cancer treatment.
12. (canceled)
13. The method of claim 1, wherein said response is a complete response, partial response no response, a pathological complete response, at least 5 year survival, or a relapse-free survival.
14-16. (canceled)
17. The method of claim 1, wherein the interpretation function is based upon a predictive model.
18. The method of claim 17, wherein the predictive model is a logistical regression model, wherein the logistic regression model is applied to the dataset to interpret the dataset to produce the predictive score, wherein a predictive score above a specified cut-off value predicts responsiveness and a predictive score below a specified cut-off predicts non-responsiveness.
19. (canceled)
20. The method of claim 19, wherein the specified cut-off is selected from the group consisting of 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, and 0.9.
21.-23. (canceled)
24. The method of claim 1, wherein the patient diagnosed with breast cancer has an ER-positive breast cancer, ER-negative breast cancer, a breast cancer characterized as Luminal B, a breast cancer characterized as basal-like, or a triple-negative breast cancer.
25-28. (canceled)
29. The method of claim 1, wherein the cancer treatment is adjuvant chemotherapy andor neoadjuvant chemotherapy.
30. The method of claim 1, wherein the cancer treatment is a treatment selected from the group consisting of: TFAC (combination of taxolfluorouracilanthracyclinecyclophosphamide) TAC (taxolanthracyclinecyclophosphamide with or without filgrastim support), ACMF (doxorubicin followed by cyclophosphamide, methotrexate, fluorouracil), ACT (doxorubicin, cyclophosphamide followed by taxol or docetaxel), A-T-C (doxorubicin followed by paclitaxel followed by cyclophosphamide), CAFFAC (fluorouracildoxorubicincyclophosphamide), CEF (cyclophosphamideepirubicinfluorouracil), AC (doxorubicincyclophosphamide), EC (epirubicincyclophosphamide), AT (doxorubicindocetaxel or doxorubicintaxol), CMF (cyclophosphamidemethotrexatefluorouracil), cyclophosphamide (Cytoxan or Neosar), methotrexate, fluorouracil (5-FU), doxorubicin (Adriamycin), epirubicin (Ellence), gemcitabine, taxol (Paclitaxel), GT (gemcitabinetaxol), taxotere (Docetaxel), vinorelbine (Navelbine), capecitabine (Xeloda), platinum drugs (Cisplatin, Carboplatin), etoposide, and vinblastine.
31-36. (canceled)
37. The method of claim 1, the method further comprising extracting RNA from breast epithelial cells.
38. The method of claim 1, the method further comprising hybridizing the sample with one or more probes to produce the expression data.
39. The method of claim 1, the method further comprising performing polymerase chain reaction to produce the expression.
40. (canceled)
41. A system for predicting a response to a cancer treatment comprising a storage memory for storing a dataset associated with a sample obtained from the subject, wherein the dataset comprises expression data for at least one marker selected from the group consisting of FLJ10517, HCAP-G, CDKN3, STK6, FOXM1, FLJ10540, TNFRSF6B, HBP17, C1QDC1, TUBG1, FLJ10036, RRM2, ACTB, ACTN1, EPHA2, TRIP13, CKS2, VRK1, DUSP4, EIF4A1, SERPINE2, and ODC1; and a processor communicatively coupled to the storage memory for determining a score with an interpretation function wherein the score is predictive of response to a cancer treatment in a subject diagnosed with cancer.
42. (canceled)
43. The system of claim 41, wherein the cancer is breast cancer.
44. A kit for predicting response to a cancer treatment in a subject comprising one or more reagents for determining from a sample obtained from a subject expression data for at least one marker selected from the group consisting of FLJ10517, HCAP-G, CDKN3, STK6, FOXM1, FLJ10540, TNFRSF6B, HBP17, C1QDC1, TUBG1, FLJ10036, RRM2, ACTB, ACTN1, EPHA2, TRIP13, CKS2, VRK1, DUSP4, EIF4A1, SERPINE2, and ODC1; and instructions for using the one or more reagents to determine expression data from the sample, wherein the instructions include instructions for determining a score from the dataset wherein the score is predictive of response to the cancer treatment.
45-46. (canceled)
47. The kit of claim 44, wherein the cancer treatment is a breast cancer treatment.
48. The kit of claim 44, wherein the cancer treatment comprises a nitrogen mustard, a vinca alkaloid, an epothilones, a taxane, a mitotic inhibitor, a corticosteroid, a topoisomerase II inhibitor, a topoisomerase I inhibitor, an anti-tumor antibiotics, an anthracycline, an antimetabolite, an ethylenimine, an alkyl sulfonate, a nitrosourea, or any combination thereof.
49-50. (canceled)
51. A method for predicting a response to a cancer treatment in a patient diagnosed with cancer comprising:
isolating a sample of the cancer from the patient diagnosed with cancer;
obtaining a dataset associated with a sample derived from a patient diagnosed with cancer, wherein the dataset comprises expression data for at least one marker selected from the group consisting of FLJ10517, HCAP-G, CDKN3, STK6, FOXM1, FLJ10540, TNFRSF6B, HBP17, C1QDC1, TUBG1, FLJ10036, RRM2, ACTB, ACTN1, EPHA2, TRIP13, CKS2, VRK1, DUSP4, EIF4A1, SERPINE2, and ODC1 and at least one clinical factor; and
determining a predictive score from the dataset using an interpretation function,
wherein the interpretation function comprises is based upon a predictive model,
wherein the predictive model is a logistical regression model,
wherein the logistical regression model is applied to the dataset to interpret the dataset to produce the predictive score, and
wherein a predictive score above a specified cut-off value predicts responsiveness and a predictive score below a specified cut-off predicts non-responsiveness.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. A process for making an embossed film web, comprising:
feeding a precursor film web between a static gas pressure plenum and a forming structure comprising a plurality of discrete apertures, discrete depressions, or combinations thereof, the apertures or depressions having a depth of at least substantially equal to a thickness of the precursor web, wherein the static gas pressure plenum creates static pressure conditions;
applying a vacuum on a forming structure facing surface of the precursor film web; and
applying static pressure from the static gas pressure plenum against the precursor web opposite the forming structure creating a pressure differential across the precursor web sufficient to force the precursor web into the apertures or depressions of the forming structure, thereby forming the embossed web comprising a plurality of discrete extended elements having open proximal ends.
2. A process of claim 1, further comprising applying a pressure from a second pressure source against the precursor web opposite the forming structure sufficient to force portions of the precursor web into void volumes defined by the apertures or depressions.
3. The process of claim 2, wherein pressure is applied from the second pressure source before pressure is applied from the static gas pressure plenum.
4. The process of claim 2, wherein pressure is applied from the second pressure source after pressure is applied from the static gas pressure plenum.
5. The process of claim 2, wherein the second pressure source is selected from the group consisting of a static liquid pressure plenum, a static gas pressure plenum, a velocity gas pressure source, a velocity liquid pressure source, and a compliant substrate.