Abstract:We investigated the loss of somatic mutations in TP53 and PIK3CA in breast cancer tissue after neoadjuvant chemotherapy (NCT) and the clinical relevance of the observed mutation profiles. Samples were derived from three cohorts: Cohort 1 consisting of 206 patients undergoing NCT with matched pre-and postchemotherapy tumor tissues; Cohort 2 consisting of 158 additional patients undergoing NCT; and Cohort 3, consisting of 81 patients undergoing chemotherapy with prechemotherapy tumor tissues. In the first cohort… Show more
“…Our PIK3CA mutation rate (23.3%) was consistent with the literature, as well as our rate of different hotspot mutations [3,14,19,[22][23][24][25][26][27][28][29][30][31][32][33][34]. Also, we confirmed significant associations of different types of PIK3CA mutations with clinicopathological and molecular characteristics.…”
Section: Discussionsupporting
confidence: 91%
“…One important question is the possible effect of PIK3CA status on cancer outcome and treatment efficacy. Notably, many studies examining the prognostic significance of PIK3CA mutations in breast cancer [35] have been published, however very few included a large enough number of patients [3,14,19,[22][23][24][25][26][27][28][29][30][31][32][33][34]. Also, less than half of them [22,24,26,28,30,31,33] used data from clinical trials, thus excluding the effect of treatment heterogeneity when evaluating prognostic factors.…”
“…Our PIK3CA mutation rate (23.3%) was consistent with the literature, as well as our rate of different hotspot mutations [3,14,19,[22][23][24][25][26][27][28][29][30][31][32][33][34]. Also, we confirmed significant associations of different types of PIK3CA mutations with clinicopathological and molecular characteristics.…”
Section: Discussionsupporting
confidence: 91%
“…One important question is the possible effect of PIK3CA status on cancer outcome and treatment efficacy. Notably, many studies examining the prognostic significance of PIK3CA mutations in breast cancer [35] have been published, however very few included a large enough number of patients [3,14,19,[22][23][24][25][26][27][28][29][30][31][32][33][34]. Also, less than half of them [22,24,26,28,30,31,33] used data from clinical trials, thus excluding the effect of treatment heterogeneity when evaluating prognostic factors.…”
“…We performed macrodissection of tumor tissues to ensure that the percentage of tumor cells was 80% or more in all breast cancer specimens (18). Total RNA was isolated from 275 adjuvant TNBC samples, 33 paired adjacent normal breast tissues, and 82 CNB TNBC tissues using the Rneasy Plus Mini Kit (Qiagen).…”
While recognized as a generally aggressive disease, triplenegative breast cancer (TNBC) is highly diverse in different patients with variable outcomes. In this prospective observational study, we aimed to develop an RNA signature of TNBC patients to improve risk stratification and optimize the choice of adjuvant therapy. Transcriptome microarrays for 33 paired TNBC and adjacent normal breast tissue revealed tumor-specific mRNAs and long noncoding RNAs (lncRNA) that were associated with recurrence-free survival. Using the Cox regression model, we developed an integrated mRNA-lncRNA signature based on the mRNA species for FCGR1A, RSAD2, CHRDL1, and the lncRNA species for HIF1A-AS2 and AK124454. The prognostic and predictive accuracy of this signature was evaluated in a training set of 137 TNBC patients and then validated in a second independent set of 138 TNBC patients. In addition, we enrolled 82 TNBC patients who underwent taxane-based neoadjuvant chemotherapy (NCT) to further verify the predictive value of the signature. In both the training and validation sets, the integrated signature had better prognostic value than clinicopathologic parameters. We also confirmed the interaction between the administration of taxane-based NCT and different risk groups. In the NCT cohort, patients in the lowrisk group were more likely to achieve pathologic complete remission after taxane-based NCT (P ¼ 0.014). Functionally, we showed that HIF1A-AS2 and AK124454 promoted cell proliferation and invasion in TNBC cells and contributed there to paclitaxel resistance. Overall, our results established an integrated mRNA-lncRNA signature as a reliable tool to predict tumor recurrence and the benefit of taxane chemotherapy in TNBC, warranting further investigation in larger populations to help frame individualized treatments for TNBC patients.
“…3B) [74,76]. Several studies showed that appearance of new mutations, undetectable in the primary tumor, can arise after neoadjuvant chemotherapy (PTEN and TP53), HER2-targeted therapies (PIK3CA), and during endocrine therapy (ESR1) for metastatic breast cancer [50][51][52][53][54][77][78][79]. Even though the relative proportion of drug-resistant subclones is generally higher in the post-treatment specimens, retreating cancers with drugs on which they previously progressed often continues to produce tumor response.…”
Section: Intratumor Genomic Heterogeneity and Implications For Treatmentmentioning
Advances in DNA and RNA sequencing revealed substantially greater genomic complexity in breast cancer than simple models of a few driver mutations would suggest. Only very few, recurrent mutations or copy-number variations in cancer-causing genes have been identified. The two most common alterations in breast cancer are TP53 (affecting the majority of triple-negative breast cancers) and PIK3CA (affecting almost half of estrogen receptor-positive cancers) mutations, followed by a long tail of individually rare mutations affecting <1%–20% of cases. Each cancer harbors from a few dozen to a few hundred potentially high-functional impact somatic variants, along with a much larger number of potentially high-functional impact germline variants. It is likely that it is the combined effect of all genomic variations that drives the clinical behavior of a given cancer. Furthermore, entirely new classes of oncogenic events are being discovered in the noncoding areas of the genome and in noncoding RNA species driven by errors in RNA editing. In light of this complexity, it is not unexpected that, with the exception of HER2 amplification, no robust molecular predictors of benefit from targeted therapies have been identified. In this review, we summarize the current genomic portrait of breast cancer, focusing on genetic aberrations that are actively being targeted with investigational drugs.
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