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Kevin Kalinsky

Publications and source records attributed to Kevin Kalinsky.

2 recordsLinked to original sources

Emerging Strategies Targeting the PI3K/AKT/mTOR Pathway in HR+/HER2- Advanced Breast Cancer.

Hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) breast cancer accounts for approximately 70% of breast cancer cases. Despite recent advances with cyclin-dependent kinase 4/6 inhibitors (CDK4/6i), resistance inevitably develops, often driven by activation of the phosphatidylinositol 3-kinase (PI3K)-AKT-mammalian target of rapamycin (mTOR) pathway. Genetic alterations such as PIK3CA mutations (present in ~ 45% of HR+/HER2- tumors), AKT1 mutations, and PTEN loss contribute to endocrine resistance and poor outcomes. This review summarizes emerging strategies targeting this pathway to overcome resistance in advanced disease. Isoform-specific PI3K inhibitors, including alpelisib and inavolisib, have demonstrated clinically meaningful progression-free survival benefits in PIK3CA-mutated populations, with inavolisib showing improved tolerability and efficacy. In contrast, pan-PI3K inhibitors such as buparlisib have been constrained by toxicity. Targeting downstream signaling, AKT inhibitors have also shown benefit: capivasertib has demonstrated clinical efficacy leading to US Food and Drug Administration approval, while ipatasertib has yielded encouraging results, particularly in tumors harboring PIK3CA, AKT1, or PTEN alterations. Mammalian target of rapamycin inhibitors, notably everolimus, have shown efficacy irrespective of mutation status. The dual PI3K-mTOR inhibitor (gedatolisib) has also shown promising progression-free survival benefit in a PIK3CA wild-type population. Next-generation agents, including mutant-selective PI3Kα inhibitors and bi-steric mTOR complex 1 inhibitors, are under active investigation. Optimal sequencing of these agents alongside endocrine therapy and CDK4/6i options remain a critical question, as does integration of genomic testing to guide therapy. Future directions include rational combination strategies, improved biomarker-driven selection, and novel modalities such as proteolysis-targeting chimeras (PROTACs). Collectively, these advances aim to enhance durability of response, minimize toxicity, and improve survival in HR+/HER2- metastatic breast cancer.

Humans

Development and Validation of a Multimodal Clinical, Pathologic, and Genomic Model for Breast Cancer Recurrence.

PURPOSE: To develop and validate a multimodal recurrence-risk model integrating histology, genomic testing, and clinical variables. METHODS: We developed AI-Path, a whole-slide image biomarker for recurrence prediction trained in CALGB 9344, and validated it in three independent cohorts: TAILORx, a multi-site Chicago cohort, and the MDX-BRCA cohort. We then integrated AI-Path with Oncotype DX Recurrence Score (RS), tumor size, and nodal status into a Cox model, PathClinRS, fit using 60% of cases from TAILORx, with the remaining 40% held out for validation. The primary end point was distant recurrence-free interval. Performance was assessed using Harrell's concordance index (C-index) and Kaplan-Meier analyses. RESULTS: A total of 12,418 patients were included. In TAILORx, AI-Path outperformed RS for distant recurrence (C-index, 0.682 vs 0.647; P = .038), driven by superior prediction of late recurrence (0.656 vs 0.567; P < .001). In node-negative disease, PathClinRS outperformed RSClin in the TAILORx fitting (0.72 vs 0.70; P = .016) and validation sets (0.74 vs 0.70; P = .004). In node-positive disease, PathClinRS outperformed RSClinN+ in Chicago (0.94 vs 0.74; P < .001) and MDX-BRCA (0.71 vs 0.66; P = .004) cohorts. Compared with NATALEE eligibility, PathClinRS identified nearly twice as many high-risk node-negative patients while maintaining a comparable 10-year distant recurrence risk (16.7% vs 16.6% per NATALEE eligibility in TAILORx fitting; 21.0% vs 19.4% in TAILORx validation). PathClinRS identified 68% of intermediate risk premenopausal patients as low-risk with no evidence of chemotherapy benefit, compared to only 36% identified as low risk by standard clinicopathologic criteria. CONCLUSION: Digital histopathology provides prognostic information complementary to genomic assays and has the potential to personalize therapy beyond existing clinicogenomic tools.

Journal Article