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The purpose of this study is to learn more about personalized cancer therapy including response to treatment and side effects. Information about the tests and treatments a person received, or will receive, for their cancer will be collected from medical records to help the researchers determine whether or not patients respond better when their physicians choose to treat them according to the genetic makeup of their tumor. Optional research tests may be performed on tissue, body cavity fluid, blood or urine provided, discarded biological samples taken during routine care that would normally be disposed of and not saved, or on blood samples collected for this study. These research tests will be used to create a "profile" of the collected specimens which will describe unique characteristics about the genes involved in a person's cancer. The tests will also help researchers look for biomarkers that may help predict how people respond to treatment.
This is a correlative study of personalized medicine with retrospective and prospective components. Patient medical records will be examined for results of molecular profiling obtained through standard of care testing to help understand, in a descriptive fashion, how well molecular testing might predict response to therapy. Patient outcome parameters including, but not limited to, tumor response, time to treatment failure, patient survival, and toxicity will be analyzed, as well as pharmacodynamic (PD) and pharmacokinetic (PK) data when available. This study will also include optional research-related testing of tissue, blood, or urine specimens via a variety of simple or advanced techniques such as molecular, proteomic, and metabolic analyses for biomarker discovery or for PK and PD parameters. These specimens will be obtained from clinical specimens archived by UCSD Health System Pathology or from specimens collected via an existing IRB-approved protocol, discarded specimens, or from specimens collected for this protocol.
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| Measure | Description | Time Frame |
|---|---|---|
| Comparison of Tumor Biomarker Profiling to Treatment Outcome | Tumor molecular profiles will be correlated to treatment outcome, assessed by measures including the response rate, the rate of stable disease (SD)>6months/partial response (PR)/complete response (CR), progression-free survival (PFS), PFS ratio (comparison of the PFS used after molecular profiling to PFS on prior treatment), time to treatment failure, and overall survival. Logistic regression models (univariable and multivariables) will be used when the outcome variable is dichotomous. Kaplan-meier curves will be used for time-to event outcomes, and comparisons will be done with the log-rank test and Cox regression models. | 4 years |
| Measure | Description | Time Frame |
|---|---|---|
| Comparison of Tumor Biomarker Profiling to Toxicity Outcome | Tumor molecular profiles will be correlated to toxicity rate (serious toxic effects, primarily Grade 3 to 5 toxicity), but may also include less serious chronic toxicity. Toxicity will be assessed using NCI CTCAE, version 4.0. | 4 years |
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Inclusion Criteria:
Exclusion Criteria:
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All patients with a diagnosis of cancer or a cancer-related condition
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Lee Suzanna, MPH | Contact | (858) 534-1306 | sml012@health.ucsd.edu | |
| Michaela Doering, BS | Contact | (858) 657-7512 | mdoering@health.ucsd.edu |
| Name | Affiliation | Role |
|---|---|---|
| Shumei Kato, MD | University of California, San Diego | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| UCSD Moores Cancer Center | Recruiting | La Jolla | California | 92093 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 41567798 | Derived | Patwari A, Nishizaki D, Jensen T, DePietro P, Pabla S, Kato S, Kurzrock R. PD-L2 Landscape and Correlation with Outcome: An Immunomic Analysis. JCO Oncol Adv. 2026 Jan;3(1):e2500151. doi: 10.1200/oa-25-00151. Epub 2026 Jan 15. | |
| 40297627 | Derived | Nikanjam M, Kato S, Nishizaki D, Barkauskas DA, Pabla S, Nesline MK, Conroy JM, Naing A, Kurzrock R. ICOS and ICOS ligand: expression patterns and outcomes in oncology patients. Ther Adv Med Oncol. 2025 Apr 24;17:17588359251330514. doi: 10.1177/17588359251330514. eCollection 2025. |
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| ID | Term |
|---|---|
| D009369 | Neoplasms |
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Blood, urine, tissue, ascites, stool, tracheal aspirate, and cerebral spinal fluid
| Eisenhower Medical Center, Lucy Curci Cancer Center | Recruiting | Rancho Mirage | California | 92270 | United States |
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| Rady Children's Hospital, San Diego | Recruiting | San Diego | California | 92123 | United States |
|
| 39220298 | Derived | Jeong AR, Trando AH, Thomas SD, Riviere P, Sakowski PJ, Sokol ES, Goodman AM, Kurzrock R. Higher tumor mutational burden and PD-L1 expression correlate with shorter survival in hematologic malignancies. Ther Adv Med Oncol. 2024 Aug 28;16:17588359241273053. doi: 10.1177/17588359241273053. eCollection 2024. |
| 37637234 | Derived | Castro A, Goodman AM, Rane Z, Talwar JV, Frampton GM, Morris GP, Lippman SM, Zhang X, Kurzrock R, Carter H. Autoimmune HLA Alleles and Neoepitope Presentation Predict Post-Allogenic Transplant Relapse. J Immunother Precis Oncol. 2023 May 15;6(3):127-132. doi: 10.36401/JIPO-22-19. eCollection 2023 Aug. |
| 37619986 | Derived | Jou J, Kato S, Miyashita H, Thangathurai K, Pabla S, DePietro P, Nesline MK, Conroy JM, Rubin E, Eskander RN, Kurzrock R. Cancer-Immunity Marker RNA Expression Levels across Gynecologic Cancers: Implications for Immunotherapy. Mol Cancer Ther. 2023 Nov 1;22(11):1352-1362. doi: 10.1158/1535-7163.MCT-23-0270. |
| 36483582 | Derived | Bevins NJ, Okamura R, Montesion M, Adashek JJ, Goodman AM, Kurzrock R. Tumor Infiltrating Lymphocyte Expression of PD-1 Predicts Response to Anti-PD-1/PD-L1 Immunotherapy. J Immunother Precis Oncol. 2022 Sep 22;5(4):90-97. doi: 10.36401/JIPO-22-9. eCollection 2022 Nov. |
| 35238467 | Derived | Louie BH, Kato S, Kim KH, Lim HJ, Lee S, Okamura R, Fanta PT, Kurzrock R. Precision medicine-based therapies in advanced colorectal cancer: The University of California San Diego Molecular Tumor Board experience. Mol Oncol. 2022 Jul;16(13):2575-2584. doi: 10.1002/1878-0261.13202. Epub 2022 Apr 8. |
| 34641956 | Derived | Pham TV, Goodman AM, Sivakumar S, Frampton G, Kurzrock R. Intra-patient stability of tumor mutational burden from tissue biopsies at different time points in advanced cancers. Genome Med. 2021 Oct 12;13(1):159. doi: 10.1186/s13073-021-00979-8. |
| 34375311 | Derived | Botta GP, Kato S, Patel H, Fanta P, Lee S, Okamura R, Kurzrock R. SWI/SNF complex alterations as a biomarker of immunotherapy efficacy in pancreatic cancer. JCI Insight. 2021 Sep 22;6(18):e150453. doi: 10.1172/jci.insight.150453. |
| 33865203 | Derived | Kato S, Porter R, Okamura R, Lee S, Zelichov O, Tarcic G, Vidne M, Kurzrock R. Functional measurement of mitogen-activated protein kinase pathway activation predicts responsiveness of RAS-mutant cancers to MEK inhibitors. Eur J Cancer. 2021 May;149:184-192. doi: 10.1016/j.ejca.2021.01.055. Epub 2021 Apr 14. |
| 33427211 | Derived | Kato S, Okamura R, Adashek JJ, Khalid N, Lee S, Nguyen V, Sicklick JK, Kurzrock R. Targeting G1/S phase cell-cycle genomic alterations and accompanying co-alterations with individualized CDK4/6 inhibitor-based regimens. JCI Insight. 2021 Jan 11;6(1):e142547. doi: 10.1172/jci.insight.142547. |
| 32923144 | Derived | Nikanjam M, Riviere P, Goodman A, Barkauskas DA, Frampton G, Kurzrock R. Tumor mutational burden is not predictive of cytotoxic chemotherapy response. Oncoimmunology. 2020 Jun 24;9(1):1781997. doi: 10.1080/2162402X.2020.1781997. |
| 32881280 | Derived | Charo LM, Eskander RN, Okamura R, Patel SP, Nikanjam M, Lanman RB, Piccioni DE, Kato S, McHale MT, Kurzrock R. Clinical implications of plasma circulating tumor DNA in gynecologic cancer patients. Mol Oncol. 2021 Jan;15(1):67-79. doi: 10.1002/1878-0261.12791. Epub 2020 Sep 17. |