Tan, Aik Choon

Abstract Introduction: Underlying tumor biology in metastatic castration-resistant prostate cancer (mCRPC) is highly complex and heterogeneous. To date, mCRPC state biomarker-enriched clinical trial designs incorporating either prognostic or predictive biomarkers are limited to alterations in homologous recombination repair pathway genes. In this study, we use an integrated clinico-molecular prognostic score in mCRPC that combines plasma prognostic proteins with a plasma-based copy number alteration (CNA) risk algorithm (PMID: 40036789; PMID: 36230636) to simulate a biomarker-enriched clinical trial design. Methods: A plasma cell-free DNA (cfDNA) prognostic risk algorithm from eight CNAs (gains in AR, MYC, PIK3CA, PIK3CB; deletions in NKX3-1, TMPRSS2, TP53, ZBTB16) is combined with clinical prognostic proteins (alkaline phosphatase, lactate dehydrogenase) to generate a prognostic risk-score (RS) in three independent treatment-naïve mCRPC cohorts. Using the RS classifier, we estimate the number of high-RS patients (pts) required to be screened from an unselected mCRPC population and the number needed for enrollment to achieve adequate statistical power in a randomized trial for a predefined effect size (Hazard Ratio- 0.70; 80% power). The trial design aims to enrich High-RS pts for targeting lethal mCRPC. Trade-offs are evaluated between number of pts screened and enrolled under varying RS enrichment thresholds and degrees of enrichment. Results: The range of RS distribution in 561 mCRPC pts from three pooled datasets was 0.362-11.737. The median overall survival (OS) (months; 95% Confidence Intervals) based on risk stratification for Low-RS (≤0.8) is 46.2 (38.8-55.4); “Intermediate-risk” (RS: 0.8-2.6) is 27.1(24.3-31.5); High-Risk (RS: >2.6) is 14.9 (11.9-17.6). For a 2-year OS mCRPC endpoint, a biomarker-enriched trial restricted to pts with RS ≥2, which corresponds to the 65th percentile of the RS distribution, would require enrollment of 398 pts, after screening 1,101 mCRPC pts to achieve 80% power to detect a 0.7 treatment vs. control hazard ratio (HR). In contrast, a traditional non-enrichment clinical trial (no molecular classifier) would require 574 pts to achieve to achieve 80% power and still not achieve adequate power to detect strong treatment by risk interactions. As a pragmatic alternative, we evaluated a hybrid enrichment strategy enrolling 50% of pts from the general mCRPC population and 50% of pts with RS ≥1 (41st percentile). This biomarker enriched design which takes 50% pts with a RS of 1.0 (or more) in a trial with 24-month follow-up will require a sample size 525 patients for which 676 pts will be screened to achieve an 80% power to detect a 0.7 treatment vs. control hazard ratio. Conclusion: A plasma-based molecular classifier can be used to design an enrichment trial in biologically defined lethal mCRPC, incorporating 50% of pts with High-RS and yet balance the required sample size and number of pts to be screened enabling an adequately powered molecular classifier-based biomarker-enriched clinical trial. Citation Format: Manish Kohli, Liang Wang, Aik C. Tan, Muhammad Zaki Fadlullah, Anushka Shankar, Sumithra Mandrekar, Benjamin Haaland. Clinico-Genomic Risk Score-Based Biomarker Enrichment Clinical Trial Designs in Poor Prognosis Metastatic Castrate Resistant Prostate Cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Prostate Cancer Research and Treatment; 2026 Jan 20-22; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(2_Suppl):Abstract nr B039.

AbstractIt has been challenging to target mutant KRAS (mKRAS) in colorectal cancer (CRC) and other malignancies. Recent efforts have focused on developing inhibitors blocking molecules essential for KRAS activity. In this regard, SOS1 inhibition has arisen as an attractive approach for mKRAS CRC given its essential role as a guanine nucleotide exchange factor for this GTPase. Here, we demonstrated the translational value of SOS1 blockade in mKRAS CRC. We used CRC patient‐derived organoids (PDOs) as preclinical models to evaluate their sensitivity to SOS1 inhibitor BI3406. A combination of in silico analyses and wet lab techniques was utilized to define potential predictive markers for SOS1 sensitivity and potential mechanisms of resistance in CRC. RNA‐seq analysis of CRC PDOs revealed two groups of CRC PDOs with differential sensitivities to SOS1 inhibitor BI3406. The resistant group was enriched in gene sets involving cholesterol homeostasis, epithelial−mesenchymal transition, and TNF‐α/NFκB signaling. Expression analysis identified a significant correlation between SOS1 and SOS2 mRNA levels (Spearman's ρ 0.56, p < 0.001). SOS1/2 protein expression was universally present with heterogeneous patterns in CRC cells but only minimal to none in surrounding nonmalignant cells. Only SOS1 protein expression was associated with worse survival in patients with RAS/RAF mutant CRC (p = 0.04). We also found that SOS1/SOS2 protein expression ratio >1 by immunohistochemistry (p = 0.03) instead of KRAS mutation (p = 1) was a better predictive marker to BI3406 sensitivity of CRC PDOs, concordant with the significant positive correlation between SOS1/SOS2 protein expression ratio and SOS1 dependency. Finally, we showed that GTP‐bound RAS level underwent rebound even in BI3406‐sensitive PDOs with no change of KRAS downstream effector genes, thus suggesting upregulation of guanine nucleotide exchange factor as potential cellular adaptation mechanisms to SOS1 inhibition. Taken together, our results show that high SOS1/SOS2 protein expression ratio predicts sensitivity to SOS1 inhibition and support further clinical development of SOS1‐targeting agents in CRC.

Abstract Purpose: Thyroid cancer cell lines are valuable models but have been neglected in pancancer genomic studies. Moreover, their misidentification has been a significant problem. We aim to provide a validated dataset for thyroid cancer researchers. Experimental Design: We performed next-generation sequencing (NGS) and analyzed the transcriptome of 60 authenticated thyroid cell lines and compared our findings with the known genomic defects in human thyroid cancers. Results: Unsupervised transcriptomic analysis showed that 94% of thyroid cell lines clustered distinctly from other lineages. Thyroid cancer cell line mutations recapitulate those found in primary tumors (e.g., BRAF, RAS, or gene fusions). Mutations in the TERT promoter (83%) and TP53 (71%) were highly prevalent. There were frequent alterations in PTEN, PIK3CA, and of members of the SWI/SNF chromatin remodeling complex, mismatch repair, cell-cycle checkpoint, and histone methyl- and acetyltransferase functional groups. Copy number alterations (CNA) were more prevalent in cell lines derived from advanced versus differentiated cancers, as reported in primary tumors, although the precise CNAs were only partially recapitulated. Transcriptomic analysis showed that all cell lines were profoundly dedifferentiated, regardless of their derivation, making them good models for advanced disease. However, they maintained the BRAFV600E versus RAS-dependent consequences on MAPK transcriptional output, which correlated with differential sensitivity to MEK inhibitors. Paired primary tumor-cell line samples showed high concordance of mutations. Complete loss of p53 function in TP53 heterozygous tumors was the most prominent event selected during in vitro immortalization. Conclusions: This cell line resource will help inform future preclinical studies exploring tumor-specific dependencies.

AbstractSrc tyrosine kinases are overexpressed in pancreatic cancers, and the oral Src inhibitor saracatinib has shown antitumor activity in preclinical models of pancreas cancer. We performed a CTEP‐sponsored Phase II clinical trial of saracatinib in previously treated pancreas cancer patients, with a primary endpoint of 6‐month survival. A Simon MinMax two‐stage phase II design was used. Saracatinib (175 mg/day) was administered orally continuously in 28‐day cycles. In the unselected portion of the study, 18 patients were evaluable. Only two (11%) patients survived for at least 6 months, and three 6‐month survivors were required to move to second stage of study as originally designed. The study was amended as a biomarker‐driven trial (leucine rich repeat containing protein 19 [LRRC19] > insulin‐like growth factor‐binding protein 2 [IGFBP2] “top scoring pairs” polymerase chain reaction [PCR] assay, and PIK3CA mutant) based on preclinical data in a human pancreas tumor explant model. In the biomarker study, archival tumor tissue or fresh tumor biopsies were tested. Biomarker‐positive patients were eligible for the study. Only one patient was PIK3CA mutant in a 3′ untranslated region (UTR) portion of the gene. This patient was enrolled in the study and failed to meet the 6‐month survival endpoint. As the frequency of biomarker‐positive patients was very low (<3%), the study was closed. Although we were unable to conclude whether enriching for a subset of second/third line pancreatic cancer patients treated with a Src inhibitor based on a biomarker would improve 6‐month survival, we demonstrate that testing pancreatic tumor samples for a biomarker‐driven, multicenter study in metastatic pancreas cancer is feasible.