Identification of four snoRNAs (SNORD16, SNORA73B, SCARNA4, and SNORD49B) as novel non-invasive biomarkers for diagnosis of breast cancer.

BACKGROUND: Emerging data point to the critical role of snoRNA in the emergence of different types of cancer, but scarcely in breast cancer (BC). This study aimed to clarify the differential expressions and potential diagnostic value of SNORD16, SNORA73B, SCARNA4, and SNORD49B in BC. METHODS: We screened differential snoRNAs in BC tissues and adjacent tissues through SNORic datasets, and then we further verified them in the plasma of BC patients and healthy volunteers by quantitative polymerase chain reaction (qPCR). RESULTS: These four snoRNAs: SNORD16, SNORA73B, SCARNA4, and SNORD49B were considerably more abundant in cancerous tissues than in neighboring tissues in the TCGA database. Their plasma levels were also higher in BC and early-stage BC patients when compared to healthy controls. Furthermore, the ROC curve demonstrated that BC (AUC = 0.7521) and early-stage BC (AUC = 0.7305) might be successfully distinguished from healthy people by SNORD16, SNORA73B, SCARNA4, and SNORD49B. CONCLUSION: Plasma snoRNAs: SNORD16, SNORA73B, SCARNA4, and SNORD49B were upregulated in BC and early-stage BC and can be used as potential diagnostic markers for BC and early-stage BC.

TEP SNORD12B, SNORA63, and SNORD14E as novel biomarkers for hepatitis B virus-related hepatocellular carcinoma (HBV-related HCC).

PURPOSE: The alterations of RNA profile in tumor-educated platelets (TEPs) have been described as a novel biosource for cancer diagnostics. This study aimed to explore the potential snoRNAs in TEP as biomarkers for diagnostics of hepatitis B virus-related hepatocellular carcinoma (HBV-related HCC). METHODS: Platelets were isolated using low-speed centrifugation and subjected to a quantitative polymerase chain reaction (qPCR) for snoRNAs detection. RESULTS: Down-regulated SNORD12B and SNORD14E as well as up-regulated SNORA63 were identified in TEP from HBV-related HCC, which could act as diagnostic biomarkers for HBV-related HCC as well as the early disease. Besides, TEP SNORD12B, SNORD14E, and SNORA63 facilitate the diagnostic performance of AFP and achieve favorable diagnostics efficiency for HBV-related HCC when combined with platelet parameters. CONCLUSIONS: Aberrant expression of SNORD12B, SNORA63, and SNORD14E in TEPs could serve as the novel and non-invasive biomarkers for HBV-related HCC diagnosis.

DNA methylation profiling to determine the primary sites of metastatic cancers using formalin-fixed paraffin-embedded tissues.

Identifying the primary site of metastatic cancer is critical to guiding the subsequent treatment. Approximately 3-9% of metastatic patients are diagnosed with cancer of unknown primary sites (CUP) even after a comprehensive diagnostic workup. However, a widely accepted molecular test is still not available. Here, we report a method that applies formalin-fixed, paraffin-embedded tissues to construct reduced representation bisulfite sequencing libraries (FFPE-RRBS). We then generate and systematically evaluate 28 molecular classifiers, built on four DNA methylation scoring methods and seven machine learning approaches, using the RRBS library dataset of 498 fresh-frozen tumor tissues from primary cancer patients. Among these classifiers, the beta value-based linear support vector (BELIVE) performs the best, achieving overall accuracies of 81-93% for identifying the primary sites in 215 metastatic patients using top-k predictions (k = 1, 2, 3). Coincidentally, BELIVE also successfully predicts the tissue of origin in 81-93% of CUP patients (n = 68).

A three-snoRNA signature: SNORD15A, SNORD35B and SNORD60 as novel biomarker for renal cell carcinoma.

BACKGROUND: Accumulating evidence has confirmed the role of snoRNAs in a variety of cancer, but rare in renal cell carcinoma (RCC). This study aims to clarify the role of snoRNAs in RCC tumorigenesis and their potential as novel tumor biomarkers. MATERIALS AND METHODS: The snoRNA expression matrix was obtained from the public TCGA and SNORic databases. SNORD15A, SNORD35B and SNORD60 were selected and validated by qPCR, then analyzed combined with related clinical factors using T-test and ROC curve. RESULTS: All three snoRNAs: SNORD15A, SNORD35B and SNORD60 were significantly upregulated in cancer tissues compared to adjacent tissues from TCGA or FFPE detection. These three snoRNAs were also increased in urinary sediment (US) of RCC as well as the early-stage RCC patients compared with the healthy controls. In addition, RNase stability experiments confirmed their stable existence in US. Meanwhile, the ROC curve shows that SNORD15A, SNORD35B and SNORD60 could effectively distinguish RCC (AUC = 0.7421) and early-stage RCC (AUC = 0.7465) from healthy individuals. CONCLUSION: SNORD15A, SNORD35B and SNORD60 were upregulated in tissues and US of RCC, serving as novel potential biomarkers for RCC diagnosis.

Contents in tumor-educated platelets as the novel biosource for cancer diagnostics.

Liquid biopsy, a powerful non-invasive test, has been widely used in cancer diagnosis and treatment. Platelets, the second most abundant cells in peripheral blood, are becoming one of the richest sources of liquid biopsy with the capacity to systematically and locally respond to the presence of cancer and absorb and store circulating proteins and different types of nucleic acids, thus called "tumor-educated platelets (TEPs)". The contents of TEPs are significantly and specifically altered, empowering them with the potential as cancer biomarkers. The current review focuses on the alternation of TEP content, including coding and non-coding RNA and proteins, and their role in cancer diagnostics.

Tumor-educated platelet SNORA58, SNORA68 and SNORD93 as novel diagnostic biomarkers for esophageal cancer.

Aim: The purpose of this study was to evaluate whether tumor-educated platelet (TEP) snoRNAs could be used as a diagnostic biomarker for esophageal cancer (ESCA). Methods: Platelet precipitates were obtained from platelet-rich plasma by low-speed centrifugation, and total RNA was extracted from platelets using Trizol™ reagent. RT-qPCR was used to detect snoRNA expression, and the receiver operating characteristic was used to assess its diagnostic potential. Results: SNORA58, SNORA68 and SNORD93 were significantly upregulated in TEPs from ESCA patients and early-stage patients compared with healthy controls. Importantly, the three snoRNAs were capable of serving as circulating biomarkers of diagnostics and early diagnosis of ESCA, possessing areas under the curve of 0.846 and 0.857, respectively. Conclusion: TEP SNORA58, SNORA68 and SNORD93 could potentially serve as noninvasive biomarkers for diagnosis and early diagnosis of ESCA.

The clonal heterogeneity of colon cancer with liver metastases.

BACKGROUND: Colon cancer with liver metastases (CCLM) characterized by genetic heterogeneity is an evolutionary process leading to variations in response to selective pressure, but the underlying evolutionary models still remains unclear. METHODS: Total of 30 samples, including primary tumor and two to four matched liver metastases from 8 treatment-naïve patients with CCLM were collected, and subjected to whole-exome DNA sequencing. PyClone was used to calculate intra and inter-tumor heterogeneity, LICHeE was used to reconstruct the cancer phylogeny trees and investigate the subclonal composition. RESULTS: The genetic differences were observed between primary and metastatic lesions, as well as among multiple metastases in all patients. The natural history models of colorectal cancer in each case were identified, including parallel, linear, and branching evolution. Liver metastases could originate from primary lesions or other metastases. Pathway and process enrichment analysis also showed obvious heterogeneity and enhancement of several molecular functions. CONCLUSIONS: Our data reveal the genetic and heterogeneity between primary and metastatic lesions, as well as among multiple metastases and provide genomic evidence for clonal heterogeneity for CCLM.

SNORD88C guided 2'-O-methylation of 28S rRNA regulates SCD1 translation to inhibit autophagy and promote growth and metastasis in non-small cell lung cancer.

Small nucleolar RNAs (snoRNAs) have been shown to play critical regulatory roles in cancer development. SNORD88C, which located at the intronic region of C19orf48 in chromosome 19q.33 with a 97-nt length was screened through database and snoRNA-sequencing. We firstly verified this snoRNA was up-regulated in tissue and plasma and served as a non-invasive diagnostic biomarker; then confirmed that SNORD88C promoted proliferation and metastasis of NSCLC in vitro and in vivo. Mechanistically, SNORD88C promoted 2'-O-methylation modification at the C3680 site on 28S rRNA and in turn enhanced downstream SCD1 translation, a central lipogenic enzyme for the synthesis of MUFA that can inhibit autophagy by regulating lipid peroxidation and mTOR, providing the novel insight into the regulation of SNORD88C in NSCLC.

The modified shrinkage classification modes could help to guide breast conserving surgery after neoadjuvant therapy in breast cancer.

Purpose: The traditional shrinkage classification modes might not suitable for guiding breast conserving surgery (BCS) after neoadjuvant therapy (NAT). Aim was to explore the modified shrinkage classification modes to guide BCS after NAT. Methods: From April 2010 to 2018, 104 patients were included. All patients underwent MRI examinations before and after NAT. Residual tumors were removed and divided into more than 30 tissue blocks at 5-mm intervals. After performing routine procedures for paraffin-embedded histology, we made semiserial sections (6-µm thick). The MRI and pathology 3D models were reconstructed with 3D-DOCTOR software. Combined with traditional shrinkage modes and efficacy of NAT, we derived modified shrinkage classification modes which oriented by BCS purpose: modified concentric shrinkage modes (MCSM) and modified non concentric shrinkage modes (MNCSM). The MCSM means the longest diameter of residual tumor was less than 50% and ≤2cm in comparison with the primary tumor before NAT. Other shrinkage modes were classified as MNCSM. Results: According to traditional shrinkage modes, 50 (48.1%) cases were suitable for BCS;while 70 (67.3%) cases were suitable for BCS according to the modified shrinkage modes (p=0.007). The consistency of MRI 3D reconstruction in assessing modified shrinkage classification modes was 93.2%, while it was 61.5% when assessing traditional shrinkage modes. Multivariate analysis showed that primary tumor stage, mammographic malignant calcification, molecular subtypes and nodal down-staging after NAT were independent predictors of modified shrinkage modes (all p<0.05). A nomogram was created based on these four predictors. With a median follow-up time of 77 months, the recurrence/metastasis rate in the MCSM and MNCSM group was 7.1% and 29.4%, respectively. Conclusion: Modified shrinkage classification modes could help to guide the individualized selection of BCS candidates and scope of resection after NAT. MRI 3D reconstruction after NAT could accurately predict modified shrinkage modes and extent of residual tumor.

Plasma exosomal tRNA-derived fragments as diagnostic biomarkers in non-small cell lung cancer.

Background: tRNA derived small RNAs (tRFs) have recently received extensive attention; however, the effects of tRFs in exosome as biomarkers has been less studied. The objective of this study was to validate novel diagnostic exosomal tRFs with sensitivity and specificity for non-small cell lung cancer (NSCLC). Methods: Exosomes extracted from plasma of NSCLC patients and healthy individuals were identified by transmission electron microscopy (TEM), qNano and western blots. The differentially expressed tRFs were screened by high-throughput sequencing in plasma exosomes of NSCLC patients and healthy individuals, and further verified by Quantitative Real-Time PCR (qRT-PCR). To assess the diagnostic efficacy of exosomal tRFs for NSCLC, receiver operating characteristic (ROC) curves were used next. Results: The expression levels of exosomal tRF-Leu-TAA-005, tRF-Asn-GTT-010, tRF-Ala-AGC-036, tRF-Lys-CTT-049, and tRF-Trp-CCA-057 were significantly decreased in NSCLC patients and early-stage NSCLC patients compared to healthy individuals. Notably, the exepression of tRF-Leu-TAA-005, tRF-Asn-GTT-010, tRF-Ala-AGC-036, tRF-Lys-CTT-049, and tRF-Trp-CCA-057 in the exosomes were higher than the exosome depleted supernatant (EDS). Conclusions: Our results showed that the levels of exosomal tRF-Leu-TAA-005, tRF-Asn-GTT-010, tRF-Ala-AGC-036, tRF-Lys-CTT-049, and tRF-Trp-CCA-057 were significantly downregulated in NSCLC patients. This suggests that these five exosomal tRFs may be promising diagnostic biomarkers for NSCLC.

Plasma SNORD42B and SNORD111 as potential biomarkers for early diagnosis of non-small cell lung cancer.

BACKGROUND: Non-small-cell lung cancer (NSCLC) still occupied the leading reason of cancer death due to lack of availability of early detection. This study aimed to identify the effective biomarkers for the early-stage NSCLC diagnostics based on plasma snoRNAs. MATERIALS AND METHODS: The differential snoRNAs between lung cancer patients and healthy donors were analyzed using the SNORic and TCGA databases. SNORD42B and SNORD111 were screened out and further verified in 48 FFPE NSCLC and adjacent normal tissues, as well as in plasma from 165 NSCLC patients and 118 health donors using qRT-PCR. Next, their diagnostic efficiency, as well as combined with carcinoembryonic antigen (CEA), was obtained by the analysis of receiver operating characteristic (ROC). RESULTS: We first screened out 47 top differential snoRNAs, among which the top 10 upregulated snoRNAs in LUAD were U44, U75, U78, U77, SNORD72, SNORD13, SNORD12B, SCARNA5, U80, SNORD41, and in LUSC were U44, U75, U78, SNORD41, SNORD111, SNORA56, U17a, SNORD35A, SNORD32A, SNORA71D. SNORD42B and SNORD111 was significantly increased not only in tumor tissues but also in plasma from NSCLC and early-stage NSCLC patients. They were capable to act as promising biomarkers for NSCLC and early-stage NSCLC diagnosis. Moreover, CEA diagnostic efficiency for early-stage NSCLC was significantly improved when combined with these two plasma snoRNAs. CONCLUSION: SNORD42B and SNORD111 could act as the potential and non-invasive diagnostic biomarkers for NSCLC and early-stage NSCLC.

Identification of Diagnostic Exosomal LncRNA-miRNA-mRNA Biomarkers in Colorectal Cancer Based on the ceRNA Network.

Background: Colorectal cancer (CRC) is currently the fourth most common cancer worldwide. The roles of exosomal competing endogenous RNAs (ceRNAs) in CRC remain unclear. In this study, we constructed an exosomal ceRNA network to identify the core ceRNAs and investigate the diagnostic biomarkers in CRC. Methods and Patients: Serum exosomes were isolated from four CRC patients and two healthy donors by ultracentrifugation, and then subjected to RNA isolation, sequencing and microarray. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) analyses were performed to identify functional enrichment implications of differentially expressed exosomal mRNAs. TargetScan and miRanda were used for identifying the miRNA-mRNA and miRNA-LncRNA interactions. The predicted lncRNAs and mRNAs were intersected with the differentially expressed genes, for which the screening criterion was fold change >1.5 in the microarray. Differentially expressed exosomal miRNAs were identified in the GSE71008 dataset, and differentially expressed mRNAs (DEmRNAs) were further summarized from The Cancer Genome Atlas (TCGA) database. Results: A total of 1186 exosomal DEmRNAs, 2088 exosomal DElncRNAs and 29 exosomal miRNAs were detected in CRC patients compared to the healthy donors. Functional enrichment analysis suggested that exosomal DEmRNAs might participate in pathways related to carcinogenesis and development of cancer. An exosomal ceRNA regulatory network of CRC was constructed based on 40 lncRNAs, two miRNAs, and five mRNAs. Exosomal miR-150-5p and miR-10b-5p expression levels were increased in healthy donors compared with CRC patients in the GSE71008 dataset, and five DEmRNAs (TOMM70A, RBM48, BEND3, RHOBTB1, and ADAMTS2) were significantly upregulated in TCGA database. Two potential exosomal regulatory axes of lncRNA G016261-miR-150-5p-RBM48 and lncRNA XLOC_011677-miR-10b-5p-BEND3 were identified from the network. Conclusion: The current study revealed potential molecular biological regulation pathways and diagnostic biomarkers through the exosomal ceRNA regulatory network.

Prognostic Characteristics of Immune-Related Genes and the Related Regulatory Axis in Patients With Stage N+M0 Breast Cancer.

Breast cancer (BRCA) has the highest incidence rate among female tumours. The function of the immune system affects treatment efficacy and prognosis in patients with BRCA. However, the exact role of immune-related genes (IRGs) in stage N+M0 BRCA is unknown. We constructed a predictive risk scoring model with five IRGs (CDH1, FGFR3, INHBA, S100B, and SCG2) based on the clinical, mutation, and RNA sequencing data of individuals with stage N+M0 BRCA sourced from The Cancer Genome Atlas. Results from the Shandong Cancer Hospital and Institute validation cohort suggested that regardless of clinical stage, tumour size, or the number of lymph node metastases, this model was able to reliably discriminate low-risk patients from high-risk ones and assess the prognosis of patients with stage N+M0 BRCA, and low-risk patients could benefit more from immunotherapy than high-risk patients. In addition, significant inter-group variations in immunocyte infiltration and the tumour microenvironment were observed. Moreover, risk score and age were found to be independent factors in multivariate COX regression analysis, which influenced the outcome of patients with stage N+M0 BRCA. Based on the above findings, we plotted a prognostic nomogram. Finally, we constructed a lncRNA KCNQ1OT1-LINC00665-TUG1/miR-9-5p/CDH1 regulatory axis of the ceRNA network to explore the mechanism of BRCA progression. In summary, we conducted a systemic and extensive bioinformatics investigation and established an IRG-based prognostic scoring model. Finally, we constructed a ceRNA regulatory axis that might play a significant role in BRCA development. More research is required to confirm this result. Scoring system-based patient grouping can help predict the outcome of patients with stage N+M0 BRCA more effectively and determine their sensitivity to immunotherapies, which will aid the development of personalised therapeutic strategies and inspire the research and development of novel medications.

Liensinine Inhibits Cell Growth and Blocks Autophagic Flux in Nonsmall-Cell Lung Cancer.

Liensinine is a bioactive component of Plumula Nelumbinis extracted from the green embryo of the mature seeds of Nelumbonaceae and exhibits therapeutic functions and noteworthy anti-tumor effects in recent studies. However, the potential anti-tumor property and the underlying mechanisms of liensinine in nonsmall-cell lung cancer (NSCLC) have not been illustrated. In this study, we demonstrated that liensinine has the potential anti-tumor property, and it could inhibit growth of NSCLC in vitro and in vivo. In addition, we found that although it induced significant accumulation of autophagosomes, liensinine could quench them for degradation and blocked autophagic flux. Importantly, we observed that liensinine inhibited the normal function of mitochondrial energy supply and impaired the lysosomal function. This research firstly provides a possibility insight that liensinine could be a novel therapeutic strategy for NSCLC.

Construction and validation of four-metabolism related-long non-coding RNAs as potential signature in prognosis of colon cancer.

Background: Emerging evidence suggests that metabolism plays important roles in the initiation and progression of colon cancer (CC) and the outcomes of CC patients. Long non-coding RNAs (lncRNA) are key regulators of regulatory molecules linking to a wide variety of cancer cellular functions. This study aims to develop a metabolic lncRNA signature to help better predict prognosis for CC patients. Methods: In the current study, the transcriptome data and clinical data of CC was downloaded from The Cancer Genome Atlas (TCGA). Metabolism-related gene sets were downloaded from the Molecular Signatures Database (MSigDB). Differential lncRNAs related to metabolism was obtained by performing the correlations between differential expression profile of metabolic genes and lncRNAs. To construct a prognostic model of CC based on metabolism-related lncRNAs, we divided patients, whose clinical data were available, into a training set and a validation set at a ratio of 7:3. The prognostic metabolism related-lncRNA signature was established using the training set by univariate and multivariate Cox regression analysis, and the validation set was used to test the capacity of the prognostic model. The correlation between risk score and clinicopathological features, immune function GO and KEGG analysis was investigated using the entire set. Finally, GSEA pathway enrichment analysis was carried out on the entire set samples for the high- and low- risk groups. Results: We identified 604 differential lncRNAs and 252 genes related to metabolism. After univariate and multivariate Cox regression analysis, four lncRNAs were finally identified to build a signature, which was verified the effectiveness by the TCGA validation set. The multivariate Cox regression analysis showed that the risk score, age of diagnosis and T stage were independent prognostic factor for CC patients. It is shown that some immunopathogenesis, GO items and KEGG pathways demonstrated difference between high- and low- risk group. Conclusions: We developed a four-metabolism related-lncRNA signature for prognostic prediction of CC, which may help select high-risk subpopulation patients who require more aggressive therapy or intervention.

Plasma exosomal miR-320d, miR-4479, and miR-6763-5p as diagnostic biomarkers in epithelial ovarian cancer.

Background: Exosomal miRNA had been proved as the promising biomarkers for multiple cancers including epithelial ovarian cancer (EOC). This study aimed to validate the diagnostic accuracy of exosomal miR-320d, miR-4479, and miR-6763-5p for EOC. Materials and methods: Exosomes isolated from the plasma by ultracentrifugation were verified using TEM, qNano and western blot. MiRNAs sequencing was used to screen out the differential exosomal miRNAs and miR-320d, miR-4479, and miR-6763-5p were selected as candidates, which were further verified by RT-qPCR in 168 healthy donors and 161 primary EOC patients. Besides, the diagnostic accuracy of these three exosomal miRNAs were evaluated using the receiver operating characteristic curve (ROC). Results: MiRNAs sequencing revealed 95 differential exosomal miRNAs between EOC patients and healthy donors. Subsequently, exosomal miR-320d, miR-4479, and miR-6763-5p were significantly down regulated in EOC patients compared with healthy controls and benign patients. More importantly, these three miRNAs could serve as circulating diagnostics biomarkers for EOC, possessing areas under the curve (AUC) of 0.6549, 0.7781, and 0.6834, respectively. Moreover, these three exosomal miRNAs levels were closely associated with lymph node metastasis, meanwhile exosomal miR-320d and miR-4479 expression was related to tumor stage. Conclusion: Exosomal miR-320d, miR-4479, and miR-6763-5p might serve as potential biomarkers for EOC.

Plasma SNORD83A as a potential biomarker for early diagnosis of non-small-cell lung cancer.

Aim: This study aimed to access the efficacy of plasma small nucleolar RNAs in early diagnosis of non-small-cell lung cancer (NSCLC). Methods: SNORD83A was selected based on databases and further verified in 48 paired formalin-fixed, paraffin-embedded tissues, as well as in plasma from 150 NSCLC patients and 150 healthy donors. The diagnostic efficiency of plasma SNORD83A, as well as in combination with carcinoembryonic antigen, was determined by receiver operating characteristic analysis. Results: SNORD83A was significantly increased not only in tissues but also in plasma from NSCLC patients compared with those from healthy donors. Plasma SNORD83A was able to act as a diagnostic biomarker for NSCLC. The diagnostic efficiency of carcinoembryonic antigen was also significantly elevated for early-stage NSCLC when combined with SNORD83A. Conclusion: SNORD83A can serve as a diagnostic biomarker for NSCLC.

Serum exosomal miR-377-3p and miR-381-3p as diagnostic biomarkers in colorectal cancer.

Aim: This study aimed to identify specific and sensitive exosomal miRNAs in diagnosing patients with colorectal cancer (CRC). Methods: Serum exosomes were isolated from 175 CRC patients and 172 healthy donors by ultracentrifugation and identified by transmission electron microscopy, nanoparticle tracking analysis and western blotting. Exosomal miRNA expression was detected by quantitative PCR and the results analyzed by receiver operating characteristic analysis to illuminate the diagnostic accuracy. Results: Both exosomal miR-377-3p and miR-381-3p were downregulated in CRC patients as well as in early-stage patients compared with healthy donors; they could serve as circulating biomarkers of diagnosis, including early diagnosis, for CRC, possessing favorable diagnostic efficiency. Conclusion: Exosomal miR-377-3p and miR-381-3p levels were downregulated in CRC patients and may be useful as novel and specific biomarkers for the diagnosis of CRC, especially early-stage CRC.

A Three lncRNA Set: AC009975.1, POTEH-AS1 and AL390243.1 as Nodal Efficacy Biomarker of Neoadjuvant Therapy for HER-2 Positive Breast Cancer.

PURPOSE: The study aimed to explore whether the expression of lncRNAs in primary tumors could predict nodal efficacy after neoadjuvant therapy (NAT) for HER2+ breast cancer. METHODS: Total RNA was extracted from HER2+ breast cancer tissues before NAT (n=103) and from 48 pairs of cancers and para-cancers tissues that did not receive NAT. Different lncRNAs were selected by microarray, validated by qPCR, and analyzed to illuminate their potential as nodal efficacy biomarkers after NAT. RESULTS: Our results demonstrated that three lncRNA sets, lncRNA-AL390243.1, POTEH-AS1, and lncRNA-AC009975.1, were up-regulated in non-apCR tissues. The AUC value was 0.789 (95%CI: 0.703-0.876). The multivariate logistic regression analysis identified the expression of lncRNA-AL390243.1 (OR 5.143; 95% CI: 1.570-16.847), tumor type (OR 0.144; 95% CI: 0.024-0.855), and nodal stage (OR 0.507; 95% CI: 0.289-0.888) as independent predictors for apCR after NAT in HER2+ patients (all p<0.05). Then the three predictors were used to create a predictive nomogram. The AUC value was 0.859 (95%CI: 0.790-0.929). The calibration curve showed a satisfactory fit between predictive and actual observation based on internal validation with a bootstrap resampling frequency of 1000. Patients with higher expression of lncRNA-AL390243.1 had worse survival. LncRNA-AL390243.1 was up-regulated more in the nodal positive subgroup than in the nodal negative subgroup (p=0.0271). CONCLUSION: The lncRNA-AL390243.1, POTEH-AS1, and lncRNA-AC009975.1 were upregulated in non-apCR breast cancer tissues. These three lncRNAs might have the potential to be used as predictive biomarkers of nodal efficacy of HER2+ breast cancer. Further studies are required to illuminate the underlying molecular mechanisms further.

tRNA-derived fragments: tRF-Gly-CCC-046, tRF-Tyr-GTA-010 and tRF-Pro-TGG-001 as novel diagnostic biomarkers for breast cancer.

BACKGROUND: tRNA-derived fragments (tRFs) have been found to play a regulatory role in the occurrence and development of many tumors. The aim of this study was to identify the expression of tRFs in breast cancer and their ability to serve as diagnostic markers for breast cancer. METHODS: Total RNA was extracted from breast cancer and paracancerous tissues (n = 83), as well as from the sera of breast cancer patients (n = 214) and healthy donors (n = 113) using trizol reagents. Expression of tRFs was then detected by q-PCR, and analyzed using t-test and ROC to illuminate their potential as biomarkers for breast cancer. RESULTS: Our results demonstrated that tRFs: tRF-Gly-CCC-046, tRF-Tyr-GTA-010 and tRF-Pro-TGG-001 were downregulated in both tissues and sera from breast cancer patients as well as early-stage patients compared with those in the healthy donors. More importantly, the three tRFs were capable of serving as circulating biomarkers of diagnostics and early diagnosis of breast cancer, possessing areas under the curve (AUC) of 0.7871 and 0.7987, respectively. CONCLUSIONS: tRFs: tRF-Gly-CCC-046, tRF-Tyr-GTA-010 and tRF-Pro-TGG-001 are downregulated in breast cancer and early breast cancer and act as new potential biomarkers for the diagnosis and early diagnosis of breast cancer.