Background: CDK9 blockade inhibits tumor growth and progression by impairing key oncogene transcription. TP-1287 is an orally delivered phosphate prodrug of the CDK9 inhibitor alvocidib. Safety outcomes from dose escalation of a phase 1 study of TP-1287 in pts with ASTs (NCT03604783) are presented. Methods: Dose Escalation: Pts with metastatic/progressive ASTs refractory to/intolerant of established therapy received oral TP-1287 starting once daily for 14 of 21 days at 1 mg, until the 2nd dose level was reached, then twice daily (BID) for 14 of 21 days for subsequent cohorts, or continuous BID dosing for 28 days. Escalation was evaluated via a 3+3 design. Primary objectives: maximum tolerated dose and recommended phase 2 dose (RP2D). Secondary objectives: pharmacokinetics, pharmacodynamics, and antitumor activity. Dose Expansion: Pts with locally advanced/metastatic sarcoma will be treated at the RP2D. Primary objective: objective response rate. Secondary objectives: progression-free survival and safety. Results: At data cutoff (September 15, 2021), 49 pts (mean age 64.0 [37.0-84.4] y; 57.1% male; 73.5% ECOG PS 1) were enrolled/treated with TP-1287 (Dose Escalation). Three pts experienced dose-limiting toxicities (DLTs) considered possibly or probably related to study drug; 1 in the 11-mg BID group (nausea) and 2 in the 16-mg BID group (fatigue; confusion, somnolence); all resolved without sequelae. In all, 48 pts (98.0%) experienced treatment-emergent adverse events (TEAEs), most commonly fatigue, nausea, and diarrhea; 27 (55.1%) experienced a Grade ≥3 TEAE (Table); 21 (42.9%) experienced a serious adverse event; and 7 (14.3%) died ≤30 days after receiving the last dose (all deaths were considered unrelated to study drug). The RP2D was 11 mg BID continuous dosing. Conclusions: The RP2D was established as 11 mg BID continuous dosing. The dose expansion cohort is open for enrollment. Table. Safety All Patients (N=49) Adverse Events, n (%) TEAE, any Grade TEAE, Grade ≥3 Any TEAE 48 (98.0) 27 (55.1) TEAEs in ≥2 pts (any grade) and in ≥1 pt (grade ≥3) Fatigue 23 (46.9) 1 (2.0) Nausea 23 (46.9) 0 Diarrhea 20 (40.8) 4 (8.2) Decreased appetite 17 (34.7) 0 Anemia 13 (26.5) 7 (14.3) Vomiting 13 (26.5) 0 Dyspnea 10 (20.4) 1 (2.0) Edema peripheral 10 (20.4) 1 (2.0) Back pain 8 (16.3) 0 Constipation 8 (16.3) 0 Hyponatremia 7 (14.3) 0 Dehydration 6 (12.2) 0 Disease progression 6 (12.2) 6 (12.2)a Abdominal pain 5 (10.2) 1 (2.0) Dizziness 5 (10.2) 0 Headache 5 (10.2) 0 Hypokalemia 5 (10.2) 2 (4.1) Urinary tract infection 5 (10.2) 0 Anxiety 4 (8.2) 0 Arthralgia 4 (8.2) 0 Depressed level of consciousness 4 (8.2) 0 Depression 4 (8.2) 0 Fall 4 (8.2) 0 Somnolence 4 (8.2) 1 (2.0) Weight decreased 4 (8.2) 0 Abdominal distension 3 (6.1) 0 AST increased 3 (6.1) 0 Asthenia 3 (6.1) 0 Cough 3 (6.1) 0 Hypotension 3 (6.1) 1 (2.0) Lethargy 3 (6.1) 0 Myalgia 3 (6.1) 0 Neck pain 3 (6.1) 0 Pyrexia 3 (6.1) 0 Abdominal discomfort 2 (4.1) 0 ALT increased 2 (4.1) 0 Ascites 2 (4.1) 0 Cancer pain 2 (4.1) 1 (2.0) Confusional state 2 (4.1) 1 (2.0) Dysgeusia 2 (4.1) 0 Dysphagia 2 (4.1) 0 Dysuria 2 (4.1) 0 Flatulence 2 (4.1) 0 Generalized edema 2 (4.1) 1 (2.0) Hematuria 2 (4.1) 1 (2.0) Hot flush 2 (4.1) 0 Hyperbilirubinemia 2 (4.1) 0 Hypercalcemia 2 (4.1) 0 Hypocalcemia 2 (4.1) 0 Hypoesthesia 2 (4.1) 0 Hypoxia 2 (4.1) 1 (2.0) Mental status changes 2 (4.1) 1 (2.0) Musculoskeletal chest pain 2 (4.1) 0 Nasal congestion 2 (4.1) 0 Neuropathy peripheral 2 (4.1) 0 Night sweats 2 (4.1) 0 Pain 2 (4.1) 2 (4.1) Pain in extremity 2 (4.1) 0 Tachycardia 2 (4.1) 0 Thrombocytopenia 2 (4.1) 0 Tumor pain 2 (4.1) 1 (2.0) Acute kidney injury 1 (2.0) 1 (2.0) Atrial fibrillation 1 (2.0) 1 (2.0) Blood alkaline phosphatase increased 1 (2.0) 1 (2.0) Chest pain 1 (2.0) 1 (2.0) Disseminated intravascular coagulation 1 (2.0) 1 (2.0) Hemoglobin decreased 1 (2.0) 1 (2.0) Hydronephrosis 1 (2.0) 1 (2.0) Hydroureter 1 (2.0) 1 (2.0) Hyperglycemia 1 (2.0) 1 (2.0) Hypertension 1 (2.0) 1 (2.0) Malignant pleural effusion 1 (2.0) 1 (2.0) Pericardial effusion 1 (2.0) 1 (2.0) Pleural effusion 1 (2.0) 1 (2.0) Respiratory failure 1 (2.0) 1 (2.0)b Seizure 1 (2.0) 1 (2.0)c Swelling 1 (2.0) 1 (2.0) Syncope 1 (2.0) 1 (2.0) Treatment-emergent SAEs, any Grade All Patients - Any SAE 21 (42.9) SAEs in ≥2 pts Disease progression 6 (12.2) Anemia 2 (4.1) aGrade 3, n=1; Grade 5, n=5. bGrade 5. cGrade 4. ALT, alanine aminotransferase; AST, aspartate aminotransferase; pts, patients; SAE, serious adverse event; TEAE, treatment-emergent adverse event. Citation Format: Nicholas J. Vogelzang, Ben George, Nissa Ashenbramer, William J. Edenfield, Donald Richards, Mitchell E. Gross, Gil D. Fine, Pablo Martinez. Phase 1, first-in-human, dose-escalation study of oral TP-1287, a cyclin dependent kinase 9 (CDK9) inhibitor, in patients (pts) with advanced solid tumors (ASTs) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT191.

Background and Aims: This study aimed to investigate safety and efficacy of silmitasertib, an oral small molecule casein kinase 2 inhibitor, plus gemcitabine and cisplatin (G+C) versus G+C in locally advanced/metastatic cholangiocarcinoma. Approach and Results: This work is a Phase 1b/2 study (S4-13-001). In Phase 2, patients received silmitasertib 1000 mg twice daily for 10 days with G+C on Days 1 and 8 of a 21-day cycle. Primary efficacy endpoint was progression-free survival (PFS) in the modified intent-to-treat population

Background: The adoption of NGS platforms and development of targeted oncology drugs have enabled matching of patients and drugs. The authors undertook an observational, clinical study to explore the feasibility and potential clinical benefits of an upfront approach to the genomic profiling of tumors from metastatic colorectal cancer (mCRC) patients. The study sought to determine the number of drug targetable genomic changes, which occur within mCRC patients including a comparison of patients who progress early versus late. Methods: The study targeted enrollment of 50 mCRC patients within the US Oncology Network followed by collection of archival FFPE samples and genomic testing. Sample collection and processing was performed at Quintiles Central Laboratories followed by testing and bioinformatic analysis at the Quintiles Genomic Laboratory. Genomic profiling was performed on the Ion Torrent PGM following enrichment of tumor DNA via the AmpliSeq Cancer Hotspot Panel v2 assay, enriching for hotspots within 50 cancer-related genes. Clinical annotation and reporting to the doctors was provided by NofOne. Basic demographic and clinical information was collected but formal disease monitoring and follow-up was not performed. Clinicians were asked to report the impact of the genomic test report on patient recommendations. Results: The study enrolled and profiled 51 stage IV mCRC patients from July 2013 to October 2013 from 18 sites in the US. Subjects were stratified by time to progression prior to entering the study. The study population was evenly distributed across early (< 1yr) and late progressors (> 1yr) with a median age of 62. Test turn-around time averaged 15 days. 98% of the bases sequenced in the genomic analysis reached the target coverage necessary to identify 5% variant frequency in the sample. Genomic variants associated with approved therapies in mCRC were observed in 7.8% of patients while 64.7% of patients had variants associated with approved therapies in other indications. 84.3% of patients had variant associated with open clinical trials. Of these 43 patients, 32 had multiple biomarkers with associated trials. Overall, more than 100 mutations were identified including alterations in KRAS, BRAF, EGFR, PIK3CA, GNAS, TP53, APC and other genes. The number of actionable mutations was not associated with progressor status. Doctors recommended clinical trials following profiling and reporting of genomic alterations in 15 out of the 51 patients (29%), Conclusions: The outcome of this observational study demonstrates the feasibility of rapid screening and reporting of NGS genomic results targeting actionable mutations in mCRC. The lack of an association between early and late progressors, suggests that a greater sample size will be required for future studies. The reported impact on clinician recommendations indicates the value of the results to inform treatment and clinical trial decisions. Citation Format: Bradley L. Smith, Philip Breitfeld, Jennifer Cubino, Victor Weigman, Donald P. Richards, Ki Y. Chung. Feasibility study of genomic biomarker profiling for patients with metastatic colorectal cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5187. doi:10.1158/1538-7445.AM2014-5187

Introduction: A test that detects cancer signal across multiple cancer types and predicts signal (tissue) origin (SO) could aid in more efficient diagnostic workup and shorten time to cancer diagnosis in individuals with signs and symptoms.Methods: The Circulating Cell-free Genome Atlas (CCGA; NCT02889978) study is a prospective, longitudinal, multicenter, case-control study to develop and validate a multi-cancer detection test. The 2nd CCGA substudy utilized a targeted methylation-based cell-free DNA assay and machine learning algorithm and included assessment of test performance (sensitivity and SO prediction accuracy) in a subgroup of participants with clinically presenting cancers (CPCs) that were undiagnosed prior to blood draw. Specificity was assessed in the noncancer group and subgroups with confounding (nonmalignant) conditions (CCs; eg, cirrhosis) and noncancer participants enrolled in hematology clinics (HCs).Results: Specificity was 99.5% (95% confidence interval: 98.2-99.9%; 396/398), 93.8% (71.7-99.7%; 15/16), and 99.3% (96.0-100.0%; 136/137) for the noncancer group, CCs subgroup, and HCs subgroup, respectively. Overall sensitivity among those with CPCs was 66.4% (62.2-70.3%; 344/518). Sensitivity of cancer signal detection increased with increasing clinical stage (Table). SO prediction accuracy was 91.7% (88.3-94.3%; 300/327) among CPC participants with cancers detected, excluding those with multiple or unknown primaries. The test demonstrated prognostic value as detected cancer participants had worse survival probability than those not detected. Conclusions: This multi-cancer detection test detected cancer signals and predicted SO in individuals with CPCs with high specificity. These findings support further clinical development of this multi-cancer detection test that could accelerate the diagnostic resolution of symptomatic cancers. Table. Sensitivity by Clinical Stage Across Cancer Type in Clinically Presenting CancersClinical StagePositive Test/Total Cancer; Sensitivity (95% CI)All*344/518; 66.4% (62.2-70.3%)I33/122; 27.0% (20.0-35.5%)II60/102; 58.8% (49.1-67.9%)III103/121; 85.1% (77.7-90.4%)IV136/147; 92.5% (87.1-95.8%)Not expected to be staged9/21; 42.9% (24.5-63.5%)Non-informative2/4; 50.0% (15.0-85.0%)CI, confidence interval.*One participant who had a positive test result had multiple primaries with clinical stage I and not-expected-to-be-staged. Citation Format: Alan H. Bryce, Minetta C. Liu, Michael V. Seiden, David D. Thiel, Donald Richards, Carlos Becerra, Kathryn N. Kurtzman, Xiaoji Chen, Tony Wu, Quan Zhang, Jingjing Gao, Nan Zhang, Earl Hubbell, Arash Jamshidi, Eric T. Fung, Eric A. Klein. Performance of a cell-free DNA-based multi-cancer detection test as a tool for diagnostic resolution of symptomatic cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr LB058.

CCGA [NCT02889978] is the largest study of cfDNA-based early cancer detection; the first CCGA learnings from multiple cfDNA assays are reported here. This prospective, multi-center, observational study has enrolled 10,012 of 15,000 demographically-balanced participants at 141 sites. Blood was collected from participants with newly diagnosed therapy-naive cancer (C, case) and participants without a diagnosis of cancer (noncancer [NC], control) as defined at enrollment. This preplanned substudy included 878 cases, 580 controls, and 169 assay controls (n=1627) across 20 tumor types and all clinical stages. All samples were analyzed by: 1) Paired cfDNA and white blood cell (WBC)-targeted sequencing (60,000X, 507 gene panel); a joint caller removed WBC-derived somatic variants and residual technical noise; 2) Paired cfDNA and WBC whole-genome sequencing (WGS; 35X); a novel machine learning algorithm generated cancer-related signal scores; joint analysis identified shared events; and 3) cfDNA whole-genome bisulfite sequencing (WGBS; 34X); normalized scores were generated using abnormally methylated fragments. In the targeted assay, non-tumor WBC-matched cfDNA somatic variants (SNVs/indels) accounted for 76% of all variants in NC and 65% in C. Consistent with somatic mosaicism (i.e., clonal hematopoiesis), WBC-matched variants increased with age; several were non-canonical loss-of-function mutations not previously reported. After WBC variant removal, canonical driver somatic variants were highly specific to C (e.g., in EGFR and PIK3CA, 0 NC had variants vs 11 and 30, respectively, of C). Similarly, of 8 NC with somatic copy number alterations (SCNAs) detected with WGS, 4 were derived from WBCs. WGBS data revealed informative hyper- and hypo-fragment level CpGs (1:2 ratio); a subset was used to calculate methylation scores. A consistent “cancer-like” signal was observed in <1% of NC participants across all assays (representing potential undiagnosed cancers). An increasing trend was observed in NC vs stages I-III vs stage IV (nonsyn. SNVs/indels per Mb [Mean±SD] NC: 1.01±0.86, stages I-III: 2.43±3.98; stage IV: 6.45±6.79; WGS score NC: 0.00±0.08, I-III: 0.27±0.98; IV: 1.95± 2.33; methylation score NC: 0±0.50; I-III: 1.02±1.77; IV: 3.94±1.70). These data demonstrate the feasibility of achieving >99% specificity for invasive cancer, and support the promise of cfDNA assay for early cancer detection. Additional data will be presented on detected plasma:tissue variant concordance and on multi-assay modeling. Citation Format: Alexander A. Aravanis, Geoffrey R. Oxnard, Tara Maddala, Earl Hubbell, Oliver Venn, Arash Jamshidi, Ling Shen, Hamed Amini, John A. Beausang, Craig Betts, Daniel Civello, Konstantin Davydov, Saniya Fazullina, Darya Filippova, Sante Gnerre, Samuel Gross, Chenlu Hou, Roger Jiang, Byoungsok Jung, Kathryn Kurtzman, Collin Melton, Shivani Nautiyal, Jonathan Newman, Joshua Newman, Cosmos Nicolaou, Richard Rava, Onur Sakarya, Ravi Vijaya Satya, Seyedmehdi Shojaee, Kristan Steffen, Anton Valouev, Hui Xu, Jeanne Yue, Nan Zhang, Jose Baselga, Rosanna Lapham, Daron G. Davis, David Smith, Donald Richards, Michael V. Seiden, Charles Swanton, Timothy J. Yeatman, Robert Tibshirani, Christina Curtis, Sylvia K. Plevritis, Richard Williams, Eric Klein, Anne-Renee Hartman, Minetta C. Liu. Development of plasma cell-free DNA (cfDNA) assays for early cancer detection: first insights from the Circulating Cell-Free Genome Atlas Study (CCGA) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-343.