Breast cancer is the most common malignancy among women, with the highest incidence rate worldwide. Dysregulation of long noncoding RNA s during the preliminary stages of breast carcinogenesis is poorly understood. In this study, we performed RNA sequencing to identify long noncoding RNA expression profiles associated with early‐stage breast cancer. RNA sequencing was performed on six invasive ductal carcinoma (IDC) tissues along with paired normal tissue samples, seven ductal carcinoma in situ tissues, and five apparently normal breast tissues. We identified 375 differentially expressed lncRNAs (DElncRNAs) in IDC tissues compared to paired normal tissues. Antisense transcripts (~ 58%) were the largest subtype among DE lnc RNA s. About 20% of the 375 DE lnc RNA s were supported by typical split readings leveraging their detection confidence. Validation was performed in n = 52 IDC and paired normal tissue by qRT ‐ PCR for the identified targets ( ADAMTS 9‐ AS 2, EPB 41L4A‐ AS 1, WDFY 3‐ AS 2, RP 11‐295M3.4, RP 11‐161M6.2, RP 11‐490M8.1, CTB ‐92J24.3, and FAM 83H‐ AS 1). We evaluated the prognostic significance of DE lnc RNA s based on TCGA datasets and report that overexpression of FAM 83H‐ AS 1 was associated with patient poor survival. We confirmed that the downregulation of ADAMTS 9‐ AS 2 in breast cancer was due to promoter hypermethylation through in vitro silencing experiments and pyrosequencing.

Breast cancer is a major cause of cancer‐related death in women worldwide. Non‐coding RNAs are a potential resource to be used as an early diagnostic biomarker for breast cancer. Circular RNAs are a recently identified group of non‐coding RNA with a significant role in disease development with potential utility in diagnosis/prognosis in cancer. In this study, we identified 26 differentially expressed circular RNAs associated with early‐stage breast cancer. RNA sequencing and two circRNA detection tools (find_circ and DCC) were used to understand the circRNA expression signature in breast cancer. We identified hsa_circ_0006743 (circJMJD1C) and hsa_circ_0002496 (circAPPBP1) to be significantly up‐regulated in early‐stage breast cancer tissues. Co‐expression analysis identified four pairs of circRNA‐miRNA (hsa_circ_0023990 : hsa‐miR‐548b‐3p, hsa_circ_0016601 : hsa_miR‐1246, hsa_circ_0001946 : hsa‐miR‐1299 and hsa_circ_0000117:hsa‐miR‐502‐5p) having potential interaction. The miRNA target prediction and network analysis revealed mRNA possibly regulated by circRNAs. We have thus identified circRNAs of diagnostic implications in breast cancer and also observed circRNA‐miRNA interaction which could be involved in breast cancer development.

KeywordsLong non-coding RNAs; Breast cancer; ADAMTS9-AS2; FAM83H-AS1; RNA sequencing; ncRNAs Abbreviations DCIS -ductal carcinoma in situ IDC -invasive ductal carcinoma NGS -Next generation sequencing lncRNA -long non-coding RNAs lincRNA -long intergenic non-coding RNA TNBC -Triple negative breast cancers BH -Bonferroni and Benjamini-Hochberg PCA -Principal component analysis PCC -Pearson's correlation coefficient PCG-Protein coding genes AbstractBreast cancer is a common malignancy among women with the highest incidence rate worldwide. Dysregulation of long non-coding RNAs occurring in the preliminary stages of breast carcinogenesis is poorly understood. In this study, RNA sequencing was done to identify long non-coding RNA expression profiles associated with early-stage breast cancer.RNA sequencing was done in 6 invasive ductal carcinoma (IDC) tissues along with paired normal tissue samples, 7 ductal carcinoma in situ (DCIS) tissues and 5 apparently normal breast tissues. We identified 375 differentially expressed lncRNAs (DElncRNAs) in IDC tissues compared to paired normal tissues. Antisense transcripts (~58%) were the largest subtype among DElncRNAs. About 20% of the 375 DElncRNAs were supported by typical split readings leveraging their detection confidence. Validation was done in n=52 IDC and paired normal tissue by qRT-PCR for the identified targets (ADAMTS9-AS2, EPB41L4A-AS1, WDFY3-AS2, RP11-295M3.4, RP11-161M6.2, RP11-490M8.1, CTB-92J24.3 and FAM83H-AS)1. We evaluated the prognostic significance of DElncRNAs based on TCGA datasets and overexpression of FAM83H-AS1 was associated with patient poor survival. We confirmed that the down-regulation of ADAMTS9-AS2 in breast cancer was due to promoter hypermethylation through in-vitro silencing experiments and pyrosequencing.

BackgroundHereditary cancers account for 5–10% of cancers. In this study BRCA1, BRCA2 and CHEK2*(1100delC) were analyzed for mutations in 91 HBOC/HBC/HOC families and early onset breast and early onset ovarian cancer cases.MethodsPCR-DHPLC was used for mutation screening followed by DNA sequencing for identification and confirmation of mutations. Kaplan-Meier survival probabilities were computed for five-year survival data on Breast and Ovarian cancer cases separately, and differences were tested using the Log-rank test.ResultsFifteen (16%) pathogenic mutations (12 in BRCA1 and 3 in BRCA2), of which six were novel BRCA1 mutations were identified. None of the cases showed CHEK2*1100delC mutation. Many reported polymorphisms in the exonic and intronic regions of BRCA1 and BRCA2 were also seen. The mutation status and the polymorphisms were analyzed for association with the clinico-pathological features like age, stage, grade, histology, disease status, survival (overall and disease free) and with prognostic molecular markers (ER, PR, c-erbB2 and p53).ConclusionThe stage of the disease at diagnosis was the only statistically significant (p < 0.0035) prognostic parameter. The mutation frequency and the polymorphisms were similar to reports on other ethnic populations. The lack of association between the clinico-pathological variables, mutation status and the disease status is likely to be due to the small numbers.

Background: We earlier used PCR-dHPLC for mutation analysis of BRCA1 and BRCA2. In this article we report application of targeted resequencing of 30 genes involved in hereditary cancers. Materials and Methods: A total of 91 patient samples were analysed using a panel of 30 genes in the Illumina HiScan SQ system. CLCBio was used for mapping reads to the reference sequences as well as for quality-based variant detection. All the deleterious mutations were then reconfirmed using Sanger sequencing. Kaplan Meier analysis was conducted to assess the effect of deleterious mutations on disease free and overall survival. Results: Seventy four of the 91 samples had been run earlier using the PCR-dHPLC and no deleterious mutations had been detected while 17 samples were tested for the first time. A total of 24 deleterious mutations were detected, 11 in BRCA1, 4 in BRCA2, 5 in p53, one each in RAD50, RAD52, ATM and TP53BP1. Some 19 deleterious mutations were seen in patients who had been tested earlier with PCR-dHPLC [19/74] and 5/17 in the samples tested for the first time, Together with our earlier detected 21 deleterious mutations in BRCA1 and BRCA2, we now had 45 mutations in 44 patients. BRCA1c.68_69delAG;p.Glu23ValfsX16 mutation was the most common, seen in 10/44 patients. Kaplan Meier survival analysis did not show any difference in disease free and overall survival in the patients with and without deleterious mutations. Conclusions: The NGS platform is more sensitive and cost effective in detecting mutations in genes involved in hereditary breast and/or ovarian cancers.