Applied Molecular-Based Quality Control of Biobanked Samples for Multi-Omics Approach.

Biobanks are vital for high-throughput translational research, but the rapid development of novel molecular techniques, especially in omics assays, poses challenges to traditional practices and recommendations. In our study, we used biospecimens from oncological patients in Polish clinics and collaborated with the Indivumed Group. For serum/plasma samples, we monitored hemolysis, controlled RNA extraction, assessed cDNA library quality and quantity, and verified NGS raw data. Tissue samples underwent pathologic evaluation to confirm histology and determine tumor content. Molecular quality control measures included evaluating the RNA integrity number, assessing cDNA library quality and quantity, and analyzing NGS raw data. Our study yielded the creation of distinct workflows for conducting preanalytical quality control of serum/plasma and fresh-frozen tissue samples. These workflows offer customization options to suit the capabilities of different biobanking entities. In order to ensure the appropriateness of biospecimens for advanced research applications, we introduced molecular-based quality control methods that align with the demands of high-throughput assays. The novelty of proposed workflows, rooted in innovative molecular techniques, lies in the integration of these QC methods into a comprehensive schema specifically designed for high-throughput research applications.

No Association between ABCB1 G2677T/A or C3435T Polymorphisms and Survival of Breast Cancer Patients-A 10-Year Follow-Up Study in the Polish Population.

Many intensive studies are devoted to identifying novel cancer diagnostics or therapy strategies that would boost cancer therapy efficacy and recovery rates. Importantly, polymorphisms in the genes coding for ABC family proteins were considered good candidates for cancer development risk or cancer drug resistance markers. For this reason, we decided to assess the contribution of ABCB1's most common variants (i.e., G2677T/A in exon 21/rs2032582 and C3435T in exon 26/rs1045642) to the cancer therapy response in breast cancer patients. A 10-year follow-up analysis of 157 breast cancer patients was performed. Clinical assessment, ABCB1 polymorphism status, estrogen/progesterone/human epidermal receptors status, and other characteristics were compared according to the follow-up status using the Chi-square statistic. For the analysis of overall survival curves in TCGA breast cancer patients, the Xena browser was used. We show that neither 2677 nor 3435 polymorphisms contributed to the survival of breast cancer patients. Interestingly, but not surprisingly, estrogen and progesterone receptors status were good prognostic factors and positively correlated with a disease-free survival for up to 10 years. To summarize, ABCB1 polymorphisms status may be one of the numerous factors that affect cancer development. However, they may not be the critical ones when it comes to risk or recovery assessment. Consequently, they may not be treated as reliable prognostic or predictive markers in breast cancer patients' evaluation, which supports the previous findings and current knowledge.

A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC.

LncRNAs have arisen as new players in the world of non-coding RNA. Disrupted expression of these molecules can be tightly linked to the onset, promotion and progression of cancer. The present study estimated the usefulness of 14 lncRNAs (HAGLR, ADAMTS9-AS2, LINC00261, MCM3AP-AS1, TP53TG1, C14orf132, LINC00968, LINC00312, TP73-AS1, LOC344887, LINC00673, SOX2-OT, AFAP1-AS1, LOC730101) for early detection of non-small-cell lung cancer (NSCLC). The total RNA was isolated from paired fresh-frozen cancerous and noncancerous lung tissue from 92 NSCLC patients diagnosed with either adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC). The expression level of lncRNAs was evaluated by a quantitative real-time PCR (qPCR). Based on Ct and delta Ct values, logistic regression and gradient boosting decision tree classifiers were built. The latter is a novel, advanced machine learning algorithm with great potential in medical science. The established predictive models showed that a set of 14 lncRNAs accurately discriminates cancerous from noncancerous lung tissues (AUC value of 0.98 ± 0.01) and NSCLC subtypes (AUC value of 0.84 ± 0.09), although the expression of a few molecules was statistically insignificant (SOX2-OT, AFAP1-AS1 and LOC730101 for tumor vs. normal tissue; and TP53TG1, C14orf132, LINC00968 and LOC730101 for LUAD vs. LUSC). However for subtypes discrimination, the simplified logistic regression model based on the four variables (delta Ct AFAP1-AS1, Ct SOX2-OT, Ct LINC00261, and delta Ct LINC00673) had even stronger diagnostic potential than the original one (AUC value of 0.88 ± 0.07). Our results demonstrate that the 14 lncRNA signature can be an auxiliary tool to endorse and complement the histological diagnosis of non-small-cell lung cancer.

Relative levels of let-7a, miR-17, miR-27b, miR-125a, miR-125b and miR-206 as potential molecular markers to evaluate grade, receptor status and molecular type in breast cancer.

MicroRNAs (miRNAs/miRs) are a class of short, single­stranded nucleic acids, which have been investigated as potential molecular markers for various types of cancer. The gold­standard and most sensitive method for comparing miRNA levels in cancer tissues is reverse transcription­quantitative polymerase chain reaction (RT­qPCR). This technique uses stably expressed genes for normalisation. The aim of the present study was to improve this model of analysis in the context of RT­qPCR results. A total of six known miRNAs (let­7a, miR­17, miR­27b, miR­125a, miR­125b and miR­206), RNU6B RNA and five mRNAs [erb­b2 receptor tyrosine kinase 2 (ERBB2), hydroxymethylbilane synthase and polymerase (RNA) II (DNA directed) polypeptide A] were analysed pair­wise, in order to determine which biomarker pairs best correlated with the histological groups of 27 breast cancer samples. The lowest P­values and the highest area under the curve values in the receiver operating characteristic analysis were used to select the optimum ratios for discrimination among groups. Among the 21 pairs, miR­17/miR­27b and miR­125a/RNU6B best discriminated three groups of samples with different tumour grades (G classification). miR­125b/miR­206 best discriminated two groups of samples with different tumour sizes (pT), let­7a/RNU6B best discriminated two groups of samples with different lymph node status (pN), and let­7a/miR­125b best discriminated groups of samples with negative and positive oestrogen and progesterone receptor status. No pair of miRNAs was found to discriminate well between groups with either a negative or positive human epidermal growth factor receptor 2 (HER2) status. However, one miRNA/mRNA pair, miR­125a/ERBB2, discriminated HER2­negative from HER2­positive groups. The breast cancer samples investigated in the present study were grouped by immunohistological methods into three molecular classes: Luminal, HER2 positive and basal (L, H and B, respectively). In order to discern L from H and L from B, two miRNA pairs were selected: miR­125a/miR­125b and miR­125a/miR­206. In conclusion, the pair­wise method of RT­qPCR data analysis may be a reasonable alternative to the standard method of using stably expressed reference genes, such as RNU6B RNA, for normalisation. This method may increase the classification power of miRNA biomarkers in breast cancer diagnostics.

Health behaviours among women diagnosed with breast tumours.

UNLABELLED: Breast cancer (BC) is one of the most common neoplasms and the second biggest cause of death among women. The aim of the study was to investigate how separate risk factors influence the development of breast neoplasms. MATERIALS AND METHODS: The study included 200 women aged between 17 and 86 years diagnosed with breast neoplasm, who were treated at the Department of Oncological Surgery in Poznan. The study included patients who underwent an operation because of a benign or malignant breast tumor. The questionnaire was completed according to the patients' answers. The histopatological diagnosis was taken from their medical history with the patients'prior consent. The statistical analysis was performed using the Statistica programme at the Department of Computer Science and Statistics of the Poznan University of Medical Sciences. The study was accepted by the Bioethics Commission of the University. RESULTS: The correlation between working status, menopausal age, being overweight, obesity, arterial hypertension, smoking, and whether BC was observed at present or in the past. Smoking was also related to a two-fold increase in malignant cancer (OR = 1.97). A BMI above 24.5 kg/m2 was associated with a nearly three-fold increase in BC (OR = 2.61). CONCLUSIONS: The results of the study offer very important implications because some of the factors which correlated positively with BC can be modified. We may postulate that a modification to the lifestyle in the sense of giving up smoking and a well-balanced diet combined with physical activity, leading to normal weight being maintained, could have a positive effect in decreasing BC development.

Study of ABCB1 polymorphism frequency in breast cancer patients from Poland.

BACKGROUND: The accumulation of mutagenic substances in the human body may result in DNA metabolism disruption followed by carcinogenesis. As a consequence of mutations in the genes coding for transmembrane protein pumps, the intracellular concentration of xenobiotics may significantly increase. This, in turn, may provoke altered risk for cancer development. The gene known to be the most relevant in the transport of numerous compounds is ABCB1 (also known as MDR1). Numerous mutations and polymorphisms that affect the encoded protein's (PgP) function were identified in this gene. The aim of the study was to define the frequency of 2677G>A,T and 3435C>T polymorphisms in a population of Polish breast cancer patients and to estimate their contribution to cancer development. METHODS: The polymorphism frequency analysis (209 patients vs. 202 control subjects) was performed either by allele-specific amplification (2677G>A,T) or by restriction fragment length polymorphism (RFLP) using the SAU3AI restriction enzyme (3435C>T) followed by verification with hybridization probe assays in a Real-Time system and sequencing. RESULTS: In the control group the frequency of individual 2677 genotypes was: wild homozygous GG = 34%, heterozygous G/T or G/A = 52.5% and variant homozygous AA or TT = 13.5%, while the genotype frequency in the group of studied patients was 43.5, 44.5 and 12%, respectively. In the control group, the frequency of individual 3435 genotypes was: CC = 25.4%, CT = 50.2%, TT = 24.4%, while the genotype frequency in the group of studied patients was 23, 46 and 31%, respectively. CONCLUSION: Thus, no significant differences in the studied polymorphism frequencies were observed. It is then suggested that the studied polymorphisms, although probably good candidates in other tissue cancer types, might not be good predictive factors in breast cancer risk or development in Caucasians.