Multiple PIK3CA mutation clonality correlates with outcomes in taselisib + fulvestrant-treated ER+/HER2-, PIK3CA-mutated breast cancers.

BACKGROUND: Mutations in the p110α catalytic subunit of phosphatidylinositol 3-kinase (PI3K), encoded by the PIK3CA gene, cause dysregulation of the PI3K pathway in 35-40% of patients with HR+/HER2- breast cancer. Preclinically, cancer cells harboring double or multiple PIK3CA mutations (mut) elicit hyperactivation of the PI3K pathway leading to enhanced sensitivity to p110α inhibitors. METHODS: To understand the role of multiple PIK3CAmut in predicting response to p110α inhibition, we estimated the clonality of multiple PIK3CAmut in circulating tumor DNA (ctDNA) from patients with HR+/HER2- metastatic breast cancer enrolled to a prospectively registered clinical trial of fulvestrant ± taselisib, and analyzed the subgroups against co-altered genes, pathways, and outcomes. RESULTS: ctDNA samples with clonal multiple PIK3CAmut had fewer co-alterations in receptor tyrosine kinase (RTK) or non-PIK3CA PI3K pathway genes compared to samples with subclonal multiple PIK3CAmut indicating a strong reliance on the PI3K pathway. This was validated in an independent cohort of breast cancer tumor specimens that underwent comprehensive genomic profiling. Furthermore, patients whose ctDNA harbored clonal multiple PIK3CAmut exhibited a significantly higher response rate and longer progression-free survival vs subclonal multiple PIK3CAmut. CONCLUSIONS: Our study establishes clonal multiple PIK3CAmut as an important molecular determinant of response to p110α inhibition and provides rationale for further clinical investigation of p110α inhibitors alone or with rationally-selected therapies in breast cancer and potentially other solid tumor types.

ER+, HER2- advanced breast cancer treated with taselisib and fulvestrant: genomic landscape and associated clinical outcomes.

Taselisib is a potent ß-sparing phosphatidylinositol 3-kinase (PI3K) inhibitor that, with endocrine therapy, improves outcomes in phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA)-mutated (PIK3CAmut) advanced breast cancer. To understand alterations associated with response to PI3K inhibition, we analysed circulating tumour DNA (ctDNA) from participants enrolled in the SANDPIPER trial. Participants were designated as either PIK3CAmut or PIK3CA no mutation was detected (NMD) per baseline ctDNA. The top mutated genes and tumour fraction estimates identified were analysed for their association with outcomes. In participants with PIK3CAmut ctDNA treated with taselisib + fulvestrant, tumour protein p53 (TP53; encoding p53) and fibroblast growth factor receptor 1 (FGFR1) alterations were associated with shorter progression-free survival (PFS) compared to participants with NMD in these genes. Conversely, participants with PIK3CAmut ctDNA harbouring a neurofibromin 1 (NF1) alteration or high baseline tumour fraction estimate experienced improved PFS upon treatment with taselisib + fulvestrant compared to placebo + fulvestrant. Broadly, alterations in oestrogen receptor (ER), PI3K and p53 pathway genes were associated with resistance to taselisib + fulvestrant in participants with PIK3CAmut ctDNA. Altogether, we demonstrated the impact of genomic (co-)alterations on outcomes with one of the largest clinico-genomic datasets of ER+, HER2-, PIK3CAmut breast cancer patients treated with a PI3K inhibitor.

Genetic Heterogeneity and Tissue-specific Patterns of Tumors with Multiple PIK3CA Mutations.

PURPOSE: To comprehensively characterize tissue-specific and molecular subclasses of multiple PIK3CA (multi-PIK3CA) mutations and assess their impact on potential therapeutic outcomes. EXPERIMENTAL DESIGN: We profiled a pan-cancer cohort comprised of 352,392 samples across 66 tumor types using a targeted hybrid capture-based next-generation sequencing panel covering at least 324 cancer-related genes. Molecularly defined subgroups, allelic configuration, clonality, and mutational signatures were identified and tested for association with PI3K inhibitor therapeutic response. RESULTS: Multi-PIK3CA mutations are found in 11% of all PIK3CA-mutant tumors, including 9% of low tumor mutational burden (TMB) PIK3CA-mutant tumors, and are enriched in breast and gynecologic cancers. Multi-PIK3CA mutations are frequently clonal and in cis on the same allele and occur at characteristic positions across tumor types. These mutations tend to be mutually exclusive of mutations in other driver genes, and of genes in the PI3K pathway. Among PIK3CA-mutant tumors with a high TMB, 18% are multi-PIK3CA mutant and often harbor an apolipoprotein B mRNA-editing enzyme, catalytic polypeptide (APOBEC) mutational signature. Despite large differences in specific allele combinations comprising multi-PIK3CA mutant tumors, especially across cancer types, patients with different classes of multi-PIK3CA mutant estrogen receptor-positive, HER2-negative breast cancers respond similarly to PI3K inhibition. CONCLUSIONS: Our pan-tumor study provides biological insights into the genetic heterogeneity and tissue specificities of multi-PIK3CA mutations, with potential clinical utility to guide PI3K inhibition strategies.

Comparison of PIK3CA Mutation Prevalence in Breast Cancer Across Predicted Ancestry Populations.

PURPOSE: Understanding the differences in biomarker prevalence that may exist among diverse populations is invaluable to accurately forecast biomarker-driven clinical trial enrollment metrics and to advance inclusive research and health equity. This study evaluated the frequency and types of PIK3CA mutations (PIK3CAmut) detected in predicted genetic ancestry subgroups across breast cancer (BC) subtypes. METHODS: Analyses were conducted using real-world genomic data from adult patients with BC treated in an academic or community setting in the United States and whose tumor tissue was submitted for comprehensive genomic profiling. RESULTS: Of 36,151 patients with BC (median age, 58 years; 99% female), the breakdown by predicted genetic ancestry was 75% European, 14% African, 6% Central/South American, 3% East Asian, and 1% South Asian. We demonstrated that patients of African ancestry are less likely to have tumors that harbor PIK3CAmut compared with patients of European ancestry with estrogen receptor-positive/human epidermal growth factor receptor 2-negative (ER+/HER2-) BC (37% [949/2,593] v 44% [7,706/17,637]; q = 4.39E-11) and triple-negative breast cancer (8% [179/2,199] v 14% [991/7,072]; q = 6.07E-13). Moreover, we found that PIK3CAmut were predominantly composed of hotspot mutations, of which mutations at H1047 were the most prevalent across BC subtypes (35%-41% ER+/HER2- BC; 43%-61% HER2+ BC; 40%-59% triple-negative breast cancer). CONCLUSION: This analysis established that tumor PIK3CAmut prevalence can differ among predicted genetic ancestries across BC subtypes on the basis of the largest comprehensive genomic profiling data set of patients with cancer treated in the United States. This study highlights the need for equitable representation in research studies, which is imperative to ensuring better health outcomes for all.

Reversion mutations in phosphoprotein P of a codon-pair-deoptimized human respiratory syncytial virus confer increased transcription, immunogenicity, and genetic stability without loss of attenuation.

Recoding viral genomes by introducing numerous synonymous nucleotide substitutions that create suboptimal codon pairs provides new live-attenuated vaccine candidates. Because recoding typically involves a large number of nucleotide substitutions, the risk of de-attenuation is presumed to be low. However, this has not been thoroughly studied. We previously generated human respiratory syncytial virus (RSV) in which the NS1, NS2, N, P, M and SH ORFs were codon-pair deoptimized (CPD) by 695 synonymous nucleotide changes (Min A virus). Min A exhibited a global reduction in transcription and protein synthesis, was restricted for replication in vitro and in vivo, and exhibited moderate temperature sensitivity. Here, we show that under selective pressure by serial passage at progressively increasing temperatures, Min A regained replication fitness and lost its temperature sensitivity. Whole-genome deep sequencing identified numerous missense mutations in several genes, in particular ones accumulating between codons 25 and 34 of the phosphoprotein (P), a polymerase cofactor and chaperone. When re-introduced into Min A, these P mutations restored viral transcription to wt level, resulting in increased protein expression and RNA replication. Molecular dynamic simulations suggested that these P mutations increased the flexibility of the N-terminal domain of P, which might facilitate its interaction with the nucleoprotein N, and increase the functional efficiency of the RSV transcription/replication complex. Finally, we evaluated the effect of the P mutations on Min A replication and immunogenicity in hamsters. Mutation P[F28V] paradoxically reduced Min A replication but not its immunogenicity. The further addition of one missense mutation each in M and L generated a version of Min A with increased genetic stability. Thus, this study provides further insight into the adaptability of large-scale recoded RNA viruses under selective pressure and identified an improved CPD RSV vaccine candidate.

Increasing Clinical Trial Accrual via Automated Matching of Biomarker Criteria.

Successful implementation of precision oncology requires both the deployment of nucleic acid sequencing panels to identify clinically actionable biomarkers, and the efficient screening of patient biomarker eligibility to on-going clinical trials and therapies. This process is typically performed manually by biocurators, geneticists, pathologists, and oncologists; however, this is a time-intensive, and inconsistent process amongst healthcare providers. We present the development of a feature matching algorithmic pipeline that identifies patients who meet eligibility criteria of precision medicine clinical trials via genetic biomarkers and apply it to patients undergoing treatment at the Stanford Cancer Center. This study demonstrates, through our patient eligibility screening algorithm that leverages clinical sequencing derived biomarkers with precision medicine clinical trials, the successful use of an automated algorithmic pipeline as a feasible, accurate and effective alternative to the traditional manual clinical trial curation.