Chemotherapy Response In Patients Research Articles

Dual-Branch Convolutional Neural Network Based on Ultrasound Imaging in the Early Prediction of Neoadjuvant Chemotherapy Response in Patients With Locally Advanced Breast Cancer.

The early prediction of a patient’s response to neoadjuvant chemotherapy (NAC) in breast cancer treatment is crucial for guiding therapy decisions. We aimed to develop a novel approach, named the dual-branch convolutional neural network (DBNN), based on deep learning that uses ultrasound (US) images for the early prediction of NAC response in patients with locally advanced breast cancer (LABC). This retrospective study included 114 women who were monitored with US during pretreatment (NAC pre) and after one cycle of NAC (NAC1). Pathologic complete response (pCR) was defined as no residual invasive carcinoma in the breast. For predicting pCR, the data were randomly split into a training set and test set (4:1). DBNN with US images was proposed to predict pCR early in breast cancer patients who received NAC. The connection between pretreatment data and data obtained after the first cycle of NAC was considered through the feature sharing of different branches. Moreover, the importance of data in various stages was emphasized by changing the weight of the two paths to classify those with pCR. The optimal model architecture of DBNN was determined by two ablation experiments. The diagnostic performance of DBNN for predicting pCR was compared with that of four methods from the latest research. To further validate the potential of DBNN in the early prediction of NAC response, the data from NAC pre and NAC1 were separately assessed. In the prediction of pCR, the highest diagnostic performance was obtained when combining the US image information of NAC pre and NAC1 (area under the receiver operating characteristic curve (AUC): 0.939; 95% confidence interval (CI): 0.907, 0.972; F1-score: 0.850; overall accuracy: 87.5%; sensitivity: 90.67%; and specificity: 85.67%), and the diagnostic performance with the combined data was superior to the performance when only NAC pre (AUC: 0.730; 95% CI: 0.657, 0.802; F1-score: 0.675; sensitivity: 76.00%; and specificity: 68.38%) or NAC1 (AUC: 0.739; 95% CI: 0.664, 0.813; F1-score: 0.611; sensitivity: 53.33%; and specificity: 86.32%) (p<0.01) was used. As a noninvasive prediction tool, DBNN can achieve outstanding results in the early prediction of NAC response in patients with LABC when combining the US data of NAC pre and NAC1.

Inhibition of Oxidized Nucleotide Sanitation By TH1579 and Conventional Chemotherapy Cooperatively Enhance Oxidative DNA Damage and Survival in AML.

Currently, the majority of patients with acute myeloid leukemia (AML) still die of their disease due to primary resistance or relapse toward conventional reactive oxygen species (ROS)- and DNA damage-inducing chemotherapy regimens. Herein, we explored the therapeutic potential to enhance chemotherapy response in AML, by targeting the ROS scavenger enzyme MutT homolog 1 (MTH1, NUDT1), which protects cellular integrity through prevention of fatal chemotherapy-induced oxidative DNA damage. We demonstrate that MTH1 is a potential druggable target expressed by the majority of patients with AML and the inv(16)/KITD816Y AML mouse model mimicking the genetics of patients with AML exhibiting poor response to standard chemotherapy (i.e., anthracycline & cytarabine). Strikingly, combinatorial treatment of inv(16)/KITD816Y AML cells with the MTH1 inhibitor TH1579 and ROS- and DNA damage-inducing standard chemotherapy induced growth arrest and incorporated oxidized nucleotides into DNA leading to significantly increased DNA damage. Consistently, TH1579 and chemotherapy synergistically inhibited growth of clonogenic inv(16)/KITD816Y AML cells without substantially inhibiting normal clonogenic bone marrow cells. In addition, combinatorial treatment of inv(16)/KITD816Y AML mice with TH1579 and chemotherapy significantly reduced AML burden and prolonged survival compared with untreated or single treated mice. In conclusion, our study provides a rationale for future clinical studies combining standard AML chemotherapy with TH1579 to boost standard chemotherapy response in patients with AML. Moreover, other cancer entities treated with ROS- and DNA damage-inducing chemo- or radiotherapies might benefit therapeutically from complementary treatment with TH1579.

Metabolic Phenotyping Predicts Gemcitabine and Cisplatin Chemosensitivity in Patients With Cholangiocarcinoma.

Gemcitabine and cisplatin serve as appropriate treatments for patients with cholangiocarcinoma (CCA). Our previous study using histoculture drug response assay (HDRA), demonstrated individual response patterns to gemcitabine and cisplatin. The current study aimed to identify predictive biomarkers for gemcitabine and cisplatin sensitivity in tissues and sera from patients with CCA using metabolomics. Metabolic signatures of patients with CCA were correlated with their HDRA response patterns. The tissue metabolic signatures of patients with CCA revealed the inversion of the TCA cycle that is evident with increased levels of citrate and amino acid backbones as TCA cycle intermediates, and glucose which corresponds to cancer stem cell (CSC) properties. The protein expression levels of CSC markers were examined on tissues and showed the significantly inverse association with the responses of patients to cisplatin. Moreover, the elevation of ethanol level was observed in gemcitabine- and cisplatin-sensitive group. In serum, a lower level of glucose but a higher level of methylguanidine was observed in the gemcitabine-responders as non-invasive predictive biomarker for gemcitabine sensitivity. Collectively, our findings indicate that these metabolites may serve as the predictive biomarkers in clinical practice which not only predict the chemotherapy response in patients with CCA but also minimize the adverse effect from chemotherapy.

Prognostic Ferroptosis-Related lncRNA Signatures Associated With Immunotherapy and Chemotherapy Responses in Patients With Stomach Cancer.

Ferroptosis is associated with the prognosis and therapeutic responses of patients with various cancers. LncRNAs are reported to exhibit antitumor or oncogenic functions. Currently, few studies have assessed the combined effects of ferroptosis and lncRNAs on the prognosis and therapy of stomach cancer. In this study, transcriptomic and clinical data were downloaded from TCGA database, and ferroptosis-related genes were obtained from the FerrDb database. Through correlation analysis, Cox analysis, and the Lasso algorithm, 10 prognostic ferroptosis-related lncRNAs (AC009299.2, AC012020.1, AC092723.2, AC093642.1, AC243829.4, AL121748.1, FLNB-AS1, LINC01614, LINC02485, LINC02728) were screened to construct a prognostic model, which was verified in two test cohorts. Risk scores for patients with stomach cancer were calculated, and patients were divided into two risk groups. The low-risk group, based on the median value, had a longer overall survival time in the KM curve, and a lower proportion of dead patients in the survival distribution curve. Potential mechanisms and possible functions were revealed using GSEA and the ceRNA network. By integrating clinical information, the association between lncRNAs and clinical features was analyzed and several features affecting prognosis were identified. Then, a nomogram was developed to predict survival rates, and its good predictive performance was indicated by a relatively high C-index (0.67118161) and a good match in calibration curves. Next, the association between these lncRNAs and therapy was explored. Patients in the low-risk group had an immune-activating environment, higher immune scores, higher TMB, lower TIDE scores, and higher expression of immune checkpoints, suggesting they might receive a greater benefit from immune checkpoint inhibitor therapy. In addition, a significant difference in the sensitivity to mitomycin. C, cisplatin, and docetaxel, but not etoposide and paclitaxel, was observed. In summary, this model had guiding significance for prognosis and personalized therapy. It helped screen patients with stomach cancer who might benefit from immunotherapy and guided the selection of personalized chemotherapeutic drugs.

Fluid-attenuated inversion recovery diffusion-weighted imaging (DWI) for evaluating chemotherapy response in patients with acute leukemia: Comparison with conventional DWI.

At present, the diagnosis and efficacy evaluation of acute leukemia (AL) are assessed by bone marrow aspiration, which is invasive and subject to sampling errors. Therefore, there is a pressing need to develop a noninvasive and accurate imaging method to evaluate bone marrow changes in patients with AL. This study aimed to compare the apparent diffusion coefficient (ADC) values obtained from fluid-attenuated inversion recovery diffusion-weighted imaging (FLAIR-DWI) and conventional DWI in the lumbar bone marrow of patients with AL and to investigate their performance for evaluating response to induction chemotherapy. A total of 28 patients with newly diagnosed AL and 25 patients with AL after induction chemotherapy underwent MRI scans at 1.5 Tesla using a conventional DWI and a FLAIR-DWI sequence on sagittal planes covering the lumbar bone marrow. Further, the ADC values from these two sequences, denoted as ADCCON and ADCFLAIR, were measured on multiple vertebrae. The percentage of leukemia cells in bone marrow was recorded, and bone marrow aspiration was performed on treated patients to determine complete remission (CR) and nonremission (NR). ADCFLAIR [(0.453 ± 0.103) × 10-3 mm2/s] was significantly lower than ADCCON [(0.486 ± 0.096) × 10-3 mm2/s] in the 28 untreated patients (t = 3.051, P = 0.005). In the 25 treated patients, ADCFLAIR and ADCCON values [(0.566 ± 0.239) × 10-3 mm2/s] and [(0.716 ± 0.235) × 10-3 mm2/s], respectively, were higher compared with the untreated patients. The ADCCON values showed a nonsignificant difference between the CR (n = 18) and NR (n = 7) groups (t = 1.409, P = 0.305). However, the ADCFLAIR values exhibited statistically significant difference (t = 2.542, P = 0.018) between the two groups. In a receiver operator characteristic (ROC) analysis, the area under the curve (AUC) using ADCFLAIR (0.770) was larger than that of ADCCON (0.611) in distinguishing the CR and NR patients following the chemotherapy. Although both ADCCON and ADCFLAIR are sensitive to tissue changes induced by chemotherapy, FLAIR-DWI outperformed conventional DWI in separating AL patients with CR from NR after chemotherapy. A possible mechanism is that FLAIR-DWI suppresses signals from free water, making the ADC measurement more sensitive to structural changes in the bone marrow.

Predictive Value of Dual-phase 18F-FDG PET/CT in the Assessment of Neoadjuvant Chemotherapy Response in Patients with Locally Advanced Breast Cancer: A prospective Comparative Study with Dynamic Contrast-enhanced Magnetic Resonance Imaging

Predictive Value of Dual-phase 18F-FDG PET/CT in the Assessment of Neoadjuvant Chemotherapy Response in Patients with Locally Advanced Breast Cancer: A prospective Comparative Study with Dynamic Contrast-enhanced Magnetic Resonance Imaging

Identification of a novel signature based on unfolded protein response-related gene for predicting prognosis in bladder cancer

BackgroundThe unfolded protein response (UPR) served as a vital role in the progression of tumors, but the molecule mechanisms of UPR in bladder cancer (BLCA) have been not fully investigated.MethodsWe identified differentially expressed unfolded protein response-related genes (UPRRGs) between BLCA samples and normal bladder samples in the Cancer Genome Atlas (TCGA) database. Univariate Cox analysis and the least absolute shrinkage and selection operator penalized Cox regression analysis were used to construct a prognostic signature in the TCGA set. We implemented the validation of the prognostic signature in GSE13507 from the Gene Expression Omnibus database. The ESTIMATE, CIBERSORT, and ssGSEA algorithms were used to explore the correlation between the prognostic signature and immune cells infiltration as well as key immune checkpoints (PD-1, PD-L1, CTLA-4, and HAVCR2). GDSC database analyses were conducted to investigate the chemotherapy sensitivity among different groups. GSEA analysis was used to explore the potential mechanisms of UPR-based signature.ResultsA prognostic signature comprising of seven genes (CALR, CRYAB, DNAJB4, KDELR3, CREB3L3, HSPB6, and FBXO6) was constructed to predict the outcome of BLCA. Based on the UPRRGs signature, the patients with BLCA could be classified into low-risk groups and high-risk groups. Patients with BLCA in the low-risk groups showed the more favorable outcomes than those in the high-risk groups, which was verified in GSE13507 set. This signature could serve as an autocephalous prognostic factor in BLCA. A nomogram based on risk score and clinical characteristics was established to predict the over survival of BLCA patients. Furthermore, the signature was closely related to immune checkpoints (PD-L1, CTLA-4, and HAVCR2) and immune cells infiltration including CD8+ T cells, follicular helper T cells, activated dendritic cells, and M2 macrophages. GSEA analysis indicated that immune and carcinogenic pathways were enriched in high-risk group.ConclusionsWe identified a novel unfolded protein response-related gene signature which could predict the over survival, immune microenvironment, and chemotherapy response of patients with bladder cancer.

Molecular Subtyping in Prognostication of Neoadjuvant Chemotherapy Response in Patients of Locally Advanced Breast Cancer

Aim: The aim of this study is to predict the response of neoadjuvant chemotherapy (NACT) based on preoperative molecular subtyping of locally advanced breast cancer patients. Materials and Methods: The present single-blind, observational study was conducted at the tertiary health-care center of Acharya Vinoba Bhave Rural Hospital from October 2018 to September 2020. This study comprised 46 patients suffering from breast cancer with TNM stage IIIA and IIIB. The patients received either NACT with cyclophosphamide/adriamycin/5-fluorouracil or paclitaxel, respectively, followed by the standard surgical procedure of modified radical mastectomy. Baseline ultrasound was followed by Trucut biopsy of the tumor which was done with 18-G Bard Trucut biopsy needle under local anesthesia in all aseptic conditions. The specimens were collected and preserved in formalin and were sent for the assessment of tumor histological examination, Scarff-Bloom-Richardson grade, and immunohistochemistry (IHC) evaluation. Depending on the luminal status obtained by IHC preoperatively, further response to chemotherapy was assessed. Results: In the CAF group, patients with human epidermal growth factor receptor 2/neu (HER2/neu)-enriched status had (91.40% ± 7.76%) tumor response followed by luminal B status (89.33% ± 5.77%), triple-negative status (87.34% ± 9.55%), and finally luminal A status with (84.87% ± 8.11%) a statistically nonsignificant relation. In the paclitaxel group, patients with triple-negative status had a tumor response of (96.59% ± 4.48%) followed by luminal B status (96.28% ± 3.27%), HER2/neu-enriched status (91.33% ± 6.85%), and finally luminal A status (82.40% ± 11.29%) with a statistically significant relation (P = 0.023). Conclusion: It can be concluded from the results that overall, HER2/neu-enriched and triple-negative status patients showed better tumor response to NACT in both groups.

The Role of Pretreatment 18F-FDG PET/CT for Early Prediction of Neoadjuvant Chemotherapy Response in Patients with Locoregionally Advanced Nasopharyngeal Carcinoma

IntroductionTo evaluate the role of maximal standardized uptake values (SUVmax) and total lesion glycolysis (TLG) from serial 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) for early prediction of neoadjuvant chemotherapy (NAC) response in locoregionally advanced nasopharyngeal carcinoma (LANPC).MethodsA total of 121 LANPC patients who completed pretreatment 18F-FDG PET/CT between June 2017 and July 2020 were retrospectively included. The median age of all the participants was 50 years old (range: 19–74 years), with 94 (77.7%) males and 27 (22.3%) females. The SUVmax from the primary tumor site (SUVmax-PT) and the total lesion glycolysis from the primary tumor site (TLG-PT) were recorded. Tumor response was calculated according to the Response Evaluation Criteria in Solid Tumor (RECIST) 1.1 Criteria at two-week post-secondary NAC cycle. Patients who achieved an objectively partial or full reaction after two cycles of NAC were defined as ‘responders’, and patients who obtained stability or progression were classified as ‘non-responders’.ResultsAfter two cycles of NAC, 96 patients were categorized as “responders” and 25 patients as “non-responders”. The optimal thresholds of the SUVmax-PT were 11.8 and 38.5 for the TLG-PT. Non-responders were significantly associated with high SUVmax-PT (HR, 3.49; 95% CI, 1.17–10.36; p = 0.024) and TLG-PT (HR, 4.45; 95% CI, 1.44–13.78; p = 0.010) in multivariate analysis. Recursive partitioning analysis (RPA) categorized patients into three prognostic groups based on SUVmax-PT and TLG-PT: high-response group, intermediate-response group, and low-response group, with corresponding favorable response rates of 94%, 80%, and 55%, respectively. Moreover, a nomogram was created based on metabolic parameters that precisely projected an individual’s response of NAC (C-index, 0.787; 95% CI, 0.533–1.000).ConclusionPretreatment 18F-FDG PET/CT to measure SUVmax-PT and TLG-PT could be a useful non-invasive method for early indication of NAC efficacy. The nomogram based on PET/CT parameters may potentially provide direction for treatment decisions based on NAC levels.

Extracellular Matrix Characterization in Gastric Cancer Helps to Predict Prognosis and Chemotherapy Response.

The extracellular matrix (ECM) plays a central role in the formation of the tumor microenvironment. The deposition of the ECM is associated with poor prognosis in a variety of tumors. Aberrant ECM deposition could undermine the effect of chemotherapy and immunotherapy. However, there is no systematic analysis on the relationship between the ECM and prognosis or chemotherapy effect. In the present study, we applied the gene set variation analysis (GSVA) algorithm to score 2199 canonical pathways in 2125 cases of probe or sequencing data and identified the core matrisome as the driving factor in gastric cancer progression. We classified gastric cancer samples into three clusters according to the composition of the ECM and evaluated clinical and multi-omics characterization of ECM phenotypes. The ECM score was evaluated by GSVA score of core matrisome and a higher ECM score predicted poor prognosis of gastric cancer [Hazard Ratio (HR), 2.084; p-value < 2 × 10−16]. In The Cancer Genome Atlas (TCGA) cohort and KUGH, YUSH, and KUCM cohorts, we verified that patients with a low ECM score could benefit from chemotherapy. By contrast, patients with a high ECM score did not achieve satisfactory response from chemotherapy. Determining the characteristics of the ECM microenvironment might help to predict the prognosis and chemotherapy response of patients with gastric cancer, and help to resolve the enigma of chemoresistance acquisition, as well as providing inspiration to develop combination therapy.

Clinical prognostic value of circulating tumor cells in the treatment of pancreatic cancer with gemcitabine chemotherapy.

Pancreatic cancer (PC) is a highly malignant tumor type with a high early metastasis rate and no obvious symptoms. Gemcitabine is a first-line chemotherapeutic drug for PC. Since there is no distinct method to determine the efficacy of chemotherapy with gemcitabine in patients with PC, the purpose of the present study was to determine whether positivity for circulating tumor cells (CTCs) in patients with advanced PC is associated with response to gemcitabine chemotherapy and to explore whether CTCs may be used as a predictor of prognosis of patients with advanced PC undergoing chemotherapy. First, immunomagnetic microspheres (magnetic beads; MIL) were prepared to detect CTCs. The patients' clinical characteristics and survival data, as well as efficacy and adverse effects of chemotherapy, were prospectively obtained and their association with CTCs was analyzed. The results indicated that CTC-positive patients with advanced PC had a higher probability of developing resistance to gemcitabine chemotherapy than CTC-negative patients. Survival in the CTC-negative group was significantly higher than in the CTC-positive group (χ2=14.58, P<0.001). CTC-positive patients with advanced PC also had shorter progression-free survival (PFS) after chemotherapy with gemcitabine (P=0.01). In conclusion, CTC-positive patients with PC are more likely to develop gemcitabine resistance, have poor PFS and low incidence of thrombocytopenia. CTCs are expected to become a prognostic indicator for chemotherapy response in patients with PC.

Abstract 2998: Targeting resistance mechanisms in muscle invasive bladder cancer using the chicken egg chorioallantoic membrane patient-derived xenograft model

Abstract Introduction: Non-metastatic muscle invasive urothelial bladder cancer (MIBC) has a poor prognosis and standard of care (SOC) consists of neoadjuvant cisplatin-based chemotherapy (NAC) combined with cystectomy. Patients receiving SOC have at best &amp;lt;10% improvement in five-year overall survival. Residual invasive cancer following NAC has no SOC and has high mortality risk. This major clinical problem underscores gaps in our understanding resistance mechanisms and a need for reliable pre-clinical models. The chicken embryo chorioallantoic membrane (CAM) represents a rapid, scalable, and cost-effective alternative in vivo patient-derived xenograft (PDX) platform. It leverages an easily accessible engraftment scaffold and vascular-rich, immunosuppressed environments for the engraftment of PDX tumors and subsequent functional studies. Our previous proteogenomic data on MIBCs with known chemo-resistant outcomes obtained prior to NAC (pre-NAC) suggests a benefit from treatment with kinase inhibitors (KI). Use of the CAM model in this study aims to address the MIBC pre-clinical model deficit and allow for the rapid screening of therapeutics against NAC-resistant PDXs using selected KI. Methods: We employed the CAM model to expand primary MIBC tumors and tested concordance between cisplatin-based chemotherapy response of patients to matching PDX tumors. We also tested selected KI response on chemotherapy-resistant bladder cancers. PDX growth was assessed by tumor surface area quantification following a week of growth with chemotherapy and KI treatment. Hematoxylin and eosin staining coupled with in situ hybridization, immunohistochemistry for Ki67, and cleaved PARP helped identify tumor cells on the CAM as well as their proliferative and apoptotic indexes. Results: Our initial results show pre-NAC primary MIBC tumors grown on the CAM phenocopy cisplatin-based chemotherapy resistance observed in parent tumor specimens. Histological analysis confirmed engraftment and growth of bladder tumors on the CAM. Patient tumor specimens acquired after chemotherapy treatment (post-NAC) and exhibiting NAC resistance were engrafted successfully on the CAM. Such CAM PDX tumors displayed decreased tumor growth size and proliferation in response to treatment with a dual EGFR and HER2 inhibitor, but had no significant response to either CDK4/6 or FGFR inhibition. Conclusion: Our data suggests concordance between Cisplatin-based chemotherapy resistance phenotypes in primary patient tumors and CAM PDX models. Further, proteogenomic informed KI use on MIBC CAM PDX models suggests a benefit from integration of rapid in vivo testing of novel therapeutics to inform more complex, pre-clinical mouse PDX experiments for more effective clinical trial design aimed at achieving optimal precision medicine for patients with limited treatment options. Citation Format: Hugo Villanueva, Patricia Castro, Andrew G. Sikora, Seth P. Lerner. Targeting resistance mechanisms in muscle invasive bladder cancer using the chicken egg chorioallantoic membrane patient-derived xenograft model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2998.

Evaluation of Tumor Elasticity and Clinicopathologic Factors Affecting Neoadjuvant Chemotherapy Response in Patients with Breast Cancer

Evaluation of Tumor Elasticity and Clinicopathologic Factors Affecting Neoadjuvant Chemotherapy Response in Patients with Breast Cancer

A Pin1/PML/P53 axis activated by retinoic acid in NPM-1c acute myeloid leukemia.

Retinoic acid (RA) was proposed to increase survival of chemotherapy- treated patients with nucleophosmin-1 (NPM-1c)-mutated acute myeloid leukemia. We reported that, ex vivo, RA triggers NPM-1c degradation, P53 activation and growth arrest. PML organizes domains that control senescence or proteolysis. Here, we demonstrate that PML is required to initiate RA-driven NPM-1c degradation, P53 activation and cell death. Mechanistically, RA enhances PML basal expression through inhibition of activated Pin1, prior to NPM-1c degradation. Such PML induction drives P53 activation, favoring blast response to chemotherapy or arsenic in vivo. This RA/PML/P53 cascade could mechanistically explain RA-facilitated chemotherapy response in patients with NPM-1c mutated acute myeloid leukemia.

Overexpression of NF-kB as a predictor of neoadjuvant chemotherapy response in breast cancer.

Cancer cells can defend themselves against apoptosis by activating NF-κB. Nuclear factor-kappa B (NF-κB) activity has also been associated with chemotherapy resistance. We aimed to investigate the relationship between NF-κB expression and intrinsic subtypes and anthracycline-based neoadjuvant chemotherapy responses in patients with locally advanced breast cancer. This prospective cohort study examined NF-κB expression and intrinsic subtypes of breast cancer tissue using immunohistochemistry (IHC). We conducted descriptive statistical analyses as well as survival analyses. The study sample was 63 patients, of which 21 cases (33.33%) were responsive to neoadjuvant chemotherapy, and 42 cases (66.7%) werenon-responsive. There is a significant relationship between negative ER, negative PR, grading, and high Ki67 expression with NF-κB overexpression (p <0.05). No significant relationship was found betweenintrinsic subtypes andHER2 with NF-κB expression (p >0.05). A significant relationship was found between NF-κB expression and responsive chemotherapy results (p <0.01). In locally advanced breast cancer, there is a correlation between NF-B expression and response to anthracycline-based neoadjuvant chemotherapy. Patients who express NF-KB have a better response to chemotherapy than those who overexpress NF-kB.

Accuracy of Neutrophil/Lymphocyte Ratio as Predictor of Neoadjuvant Chemotherapy Response in Locally Advanced Breast Cancer at Dr. Mohammad Hoesin General Hospital Palembang

Introduction: Breast cancer is one of the most common neoplasm occurs in women. Neoadjuvant Chemotherapy (NACT) is widely used in Locally Advanced Breast Cancer (LABC) and Inflammatory Breast Cancer (IBC), to reduce tumor size (down-sizing), and further allowing breast-conserving surgery to be performed. Accurate markers are needed to prevent impractical chemotherapy that allows patients to receive definitive surgery in a timely manner. Previous study showed neutrophil/lymphocyte ratio (NLR) was superior in predicting long-term outcomes over PLR. This study aims to evaluate the relationship between the NLR value and neoadjuvant chemotherapy response in patients with locally advanced breast cancer at Dr. Mohammad Hoesin General Hospital Palembang.&#x0D; Methods: This study is a prognostic test of the NLR accuracy to predict the response of neoadjuvant chemotherapy in patients with locally advanced breast cancer. The study included 113 patients as study subjects.&#x0D; Results: The obtained NLR cut off point value was ≤ 2.92 with an area under the ROC curve (AUC) of 92.2%. The diagnostic measures of the NLR prognostic test had sensitivity of 93%, specificity of 93%, Positive Predictive Value of 97%, Negative Predictive Value of 82%, and accuracy of 93%. There is a significant relationship between NLR and chemotherapy response in patients with locally advanced breast cancer (p = 0.000).&#x0D; Conclusion: There is a significant relationship between NLTR and chemotherapy response. NLR can be used as a predictor of neoadjuvant chemotherapy response with a good degree of accuracy.

The tumor immune microenvironment and immune-related signature predict the chemotherapy response in patients with osteosarcoma

BackgroundGenome-wide expression profiles have been shown to predict the response to chemotherapy. The purpose of this study was to develop a novel predictive signature for chemotherapy in patients with osteosarcoma.MethodsWe analysed the relevance of immune cell infiltration and gene expression profiles of the tumor samples of good responders with those of poor responders from the TARGET and GEO databases. Immune cell infiltration was evaluated using a single-sample gene set enrichment analysis (ssGSEA) and the CIBERSORT algorithm between good and poor chemotherapy responders. Differentially expressed genes were identified based on the chemotherapy response. LASSO regression and binary logistic regression analyses were applied to select the differentially expressed immune-related genes (IRGs) and developed a predictive signature in the training cohort. A receiver operating characteristic (ROC) curve analysis was employed to assess and validate the predictive accuracy of the predictive signature in the validation cohort.ResultsThe analysis of immune infiltration showed a positive relationship between high-level immune infiltration and good responders, and T follicular helper cells and CD8 T cells were significantly more abundant in good responders with osteosarcoma. Two hundred eighteen differentially expressed genes were detected between good and poor responders, and a five IRGs panel comprising TNFRSF9, CD70, EGFR, PDGFD and S100A6 was determined to show predictive power for the chemotherapy response. A chemotherapy-associated predictive signature was developed based on these five IRGs. The accuracy of the predictive signature was 0.832 for the training cohort and 0.720 for the validation cohort according to ROC analysis.ConclusionsThe novel predictive signature constructed with five IRGs can be effectively utilized to predict chemotherapy responsiveness and help improve the efficacy of chemotherapy in patients with osteosarcoma.

Platelet/Lymphocyte Ratio Accuracy as Predictor of Neo-Adjuvant Chemotherapy Response in Locally Advanced Breast Cancer at Dr. Mohammad Hoesin General Hospital Palembang

Background: Platelet/lymphocyte ratio (PLR) is considered as predictor for chemotherapy response in locally advanced breast cancer undergoing neo-adjuvant chemotherapy. This study aims to evaluate the relationship between the platelet/lymphocyte ratio and neo-adjuvant chemotherapy response in patients with locally advanced breast cancer at Dr. Mohammad Hoesin General Hospital Palembang.&#x0D; Methods: This study is a prognostic test of the platelet/lymphocyte ratio accuracy to predict the response of neo-adjuvant chemotherapy in patients with locally advanced breast cancer. The study included 113 subjects.&#x0D; Results: From 113 patients, the PLR cut off point value was 206.83 with an under curve area (AUC) of 91.8%. The results of the PLR prognostic test were sensitivity of 98%, specificity of 87%, Positive Predictive Value of 95%, Negative Predictive Value of 93%, and 95% of accuracy. There was a significant relationship between PLR and chemotherapy response in patients with locally advanced breast cancer (p = 0.000).&#x0D; Conclusion: There was a significant relationship between PLR on chemotherapy response. PLR can be used as a predictor of neo-adjuvant chemotherapy response with a good degree of accuracy.

A novel gene signature for prognosis prediction and chemotherapy response in patients with pancreatic cancer.

Pancreatic cancer is a lethal disease. Chemoresistance is one of the characteristics of pancreatic cancer and leads to a poor prognosis. This study built an effective predictive model for personalized treatment and explored the molecular mechanism of chemoresistance. A four-gene signature, including serine peptidase inhibitor Kazal type 1 (SPINK1), anoctamin 1 (ANO1), desmoglein 3 (DSG3) and GTPase, IMAP family member 1 (GIMAP1) was identified and associated with prognosis and chemoresistance in the training group. An internal testing dataset and the external dataset, GSE57495, were used for validation and showed a good performance of the gene signature. The high-risk group was enriched with multiple oncological pathways related to immunosuppression and was correlated with epidermal growth factor receptor (EGFR) expression, a target molecule of Erlotinib. In conclusion, this study identified a four-gene signature and established two nomograms for predicting prognosis and chemotherapy responses in patients with pancreatic cancer. The clinical value of the nomogram was evaluated by decision curve analysis (DCA). It showed that these may be helpful for clinical treatment decision-making and the discovery of the potential molecular mechanism and therapy targets for pancreatic cancer.

Contrast enhanced ultrasound quantitative parameters for assessing neoadjuvant chemotherapy response in patients with locally advanced breast cancer.

To evaluate the role of contrast-enhanced ultrasound (CEUS) quantitative parameters in predicting neoadjuvant chemotherapy (NACT) response in patients with locally advanced breast cancer (LABC). 30 patients with histologically proven LABC scheduled for NACT were recruited. CEUS was performed using a contrast bolus of 4.8 ml and time intensity curves (TICs) were obtained by contrast dynamics software. CEUS quantitative parameters assessed were peak enhancement (PE), time-to-peak (TTP), area under the curve (AUC) and mean transit time (MTT). The parameters were documented on four consecutive instances: before NACT and 3 weeks after each of the three cycles. The gold-standard was pathological response using Miller Payne Score obtained pre NACT and post-surgery. A decrease in mean values of PE and an increase in mean values of TTP and MTT was observed with each cycle of NACT among responders. Post each cycle of NACT (compared with baseline pre-NACT), there was a statistically significant difference in % change of mean values of PE, TTP and MTT between good responders and poor responders (p-value < 0.05). The diagnostic accuracy of TTP post-third cycle was 87.2% (p = 0.03), and MTT post--second and third cycle was 76.7% (p = 0.004) and 86.7% (p = 0.006) respectively. In responders, a decrease in the tumor vascularity was reflected in the CEUS quantitative parameters as a reduction in PE, and a prolongation in TTP, MTT. Prediction of NACT response by CEUS has the potential to serve as a diagnostic modality for modification of chemotherapy regimens during ongoing NACT among patients with LABC, thus affecting patient prognosis.