Unlocking the tumor-immune microenvironment in osteosarcoma: insights into the immune landscape and mechanisms.

Osteosarcoma has a unique tumor microenvironment (TME), which is characterized as a complex microenvironment comprising of bone cells, immune cells, stromal cells, and heterogeneous vascular structures. These elements are intricately embedded in a mineralized extracellular matrix, setting it apart from other primary TMEs. In a state of normal physiological function, these cell types collaborate in a coordinated manner to maintain the homeostasis of the bone and hematopoietic systems. However, in the pathological condition, i.e., neoplastic malignancies, the tumor-immune microenvironment (TIME) has been shown to promote cancer cells proliferation, migration, apoptosis and drug resistance, as well as immune escape. The intricate and dynamic system of the TIME in osteosarcoma involves crucial roles played by various infiltrating cells, the complement system, and exosomes. This complexity is closely associated with tumor cells evading immune surveillance, experiencing uncontrolled proliferation, and facilitating metastasis. In this review, we elucidate the intricate interplay between diverse cell populations in the osteosarcoma TIME, each contributing uniquely to tumor progression. From chondroblastic and osteoblastic osteosarcoma cells to osteoclasts, stromal cells, and various myeloid and lymphoid cell subsets, the comprehensive single-cell analysis provides a detailed roadmap of the complex osteosarcoma ecosystem. Furthermore, we summarize the mutations, epigenetic mechanisms, and extracellular vesicles that dictate the immunologic landscape and modulate the TIME of osteosarcoma. The perspectives of the clinical implementation of immunotherapy and therapeutic approaches for targeting immune cells are also intensively discussed.

Targeting pediatric solid tumors in the new era of RNA therapeutics.

Despite substantial progress in pediatric cancer treatment, poor prognosis remained for patients with recurrent or metastatic disease, given the limitations of approved targeted treatments and immunotherapies. RNA therapeutics offer significant potential for addressing a broad spectrum of diseases, including cancer. Advances in manufacturing and delivery systems are paving the way for the rapid development of therapeutic RNAs for clinical applications. This review summarizes therapeutic RNA classifications and the mechanisms of action, highlighting their potential in manipulating major cancer-related pathways and biological effects. We also focus on the pre-clinical investigation of RNA molecules with efficient delivery systems for their therapeutic potential targeting pediatric solid tumors.

Establishment, characterization, and genetic profiling of patient-derived osteosarcoma cells from a patient with retinoblastoma.

Osteosarcoma is the most common malignant bone cancer in pediatric patients. Patients who respond poorly to chemotherapy experience worse clinical outcomes with a high mortality rate. The major challenge is the lack of effective drugs for these patients. To introduce new drugs for clinical approval, preclinical studies based on in vitro models must demonstrate the potency of the tested drugs, enabling the drugs to enter phase 1 clinical trials. Patient-derived cell culture is a promising testing platform for in vitro studies, as they more accurately recapitulate cancer states and genetic profiles compared to cell lines. In the present study, we established patient-derived osteosarcoma cells (PDC) from a patient who had previously been diagnosed with retinoblastoma. We identified a new variant of a germline mutation in the RB1 gene in the tissue of the patient. The biological effects of this PDC were studied to observe whether the cryopreserved PDC retained a feature of fresh PDC. The cryopreserved PDC preserved the key biological effects, including cell growth, invasive capability, migration, and mineralization, that define the conserved phenotypes compared to fresh PDC. From whole genome sequencing analysis of osteosarcoma tissue and patient-derived cells, we found that cryopreserved PDC was a minor population in the origin tissue and was selectively grown under the culture conditions. The cryopreserved PDC has a high resistance to conventional chemotherapy. This study demonstrated that the established cryopreserved PDC has the aggressive characteristics of osteosarcoma, in particular the chemoresistance phenotype that might be used for further investigation in the chemoresistant mechanism of osteosarcoma. In conclusion, the approach we applied for primary cell culture might be a promising method to generate in vitro models for functional testing of osteosarcoma.

Can conventional magnetic resonance imaging at presentation predict chemoresistance in osteosarcoma?

OBJECTIVES: Histological tumour necrosis is the current indicator for the response of osteosarcoma after neoadjuvant chemotherapy. Chemoresistant tumours require close monitoring and adjustment of treatment. Characteristics of tumours on baseline MRI may be able to predict response to chemotherapy. The aim is to identify which baseline MRI findings can help predict chemoresistant osteosarcoma. METHODS: Baseline MRI before giving neoadjuvant chemotherapy of 95 patients during 2008-2021 was reviewed by 2 musculoskeletal radiologists. Histological necrosis from surgical specimens was the reference standard. MRIs were reviewed for tumour characteristics (tumour volume, maximum axial diameter, central necrosis, haemorrhage, fluid-fluid level), peritumoural bone and soft tissue oedema, and other parameters including intra-articular extension, epiphyseal involvement, neurovascular involvement, pathologic fracture, and skip metastasis. The cut-off thresholds were generated by receiver operating characteristic curves which then tested for diagnostic accuracy. RESULTS: Two-third of patients were chemoresistance (histological necrosis <90%). Tumour volume >150 mL, maximum axial diameter >7.0 cm, area of necrosis >50%, presence of intra-articular extension, and peritumoural soft tissue oedema >6.5 cm significantly predicted chemoresistance, particularly when found in combination. Tumour volume >150 mL and maximum axial diameter >7.0 cm could be used as an independent predictor (multivariable analysis, P-value = .025, .045). CONCLUSIONS: Findings on baseline MRI could help predicting chemoresistant osteosarcoma with tumour size being the strongest predictor. ADVANCES IN KNOWLEDGE: Osteosarcomas with large size, large cross-sectional diameter, large area of necrosis, presence of intra-articular extension, and extensive peritumoural soft tissue oedema were most likely to have a poor response to neoadjuvant chemotherapy.

Deciphering the Biology of Circulating Tumor Cells through Single-Cell RNA Sequencing: Implications for Precision Medicine in Cancer.

Circulating tumor cells (CTCs) hold unique biological characteristics that directly involve them in hematogenous dissemination. Studying CTCs systematically is technically challenging due to their extreme rarity and heterogeneity and the lack of specific markers to specify metastasis-initiating CTCs. With cutting-edge technology, single-cell RNA sequencing (scRNA-seq) provides insights into the biology of metastatic processes driven by CTCs. Transcriptomics analysis of single CTCs can decipher tumor heterogeneity and phenotypic plasticity for exploring promising novel therapeutic targets. The integrated approach provides a perspective on the mechanisms underlying tumor development and interrogates CTCs interactions with other blood cell types, particularly those of the immune system. This review aims to comprehensively describe the current study on CTC transcriptomic analysis through scRNA-seq technology. We emphasize the workflow for scRNA-seq analysis of CTCs, including enrichment, single cell isolation, and bioinformatic tools applied for this purpose. Furthermore, we elucidated the translational knowledge from the transcriptomic profile of individual CTCs and the biology of cancer metastasis for developing effective therapeutics through targeting key pathways in CTCs.

Effects of glyphosate-based herbicides and glyphosate exposure on sex hormones and the reproductive system: From epidemiological evidence to mechanistic insights.

Glyphosate-based herbicides (GBHs) containing glyphosate as the active component are extensively used worldwide. Concerns have arisen about their potential risk to human, as glyphosate has been detected in human body fluids. Current controversies surround the endocrine-disrupting properties and transgenerational inheritance of diseases and germline epimutations resulting from exposure to GBHs and glyphosate. This review discusses evidence from in vitro, in vivo, and clinical studies on their impact on sex hormone regulation and reproductive system. Evidence suggests that they act as endocrine-disrupting chemicals, which altering sex hormone levels. Mechanistically, they interfere with hormone signaling pathways by disrupting proteins involved in hormone transport and metabolism. Pathological changes have been observed in male and female reproductive systems, potentially leading to reproductive toxicity. Prenatal exposure may lead to transgenerational inheritance of pathologies and sperm epimutations. However, due to the complexity of glyphosate formulations containing adjuvants identifying higher risk components in environmental exposure becomes challenging.

Validation of a Diagnostic Model to Differentiate Multiple Myeloma from Bone Metastasis.

Purpose: A diagnostic model to differentiate multiple myeloma (MM) from bone metastasis (BM) in patients with destructive bone lesions (MM-BM DDx) was developed to promote timely and appropriate referral of patients with MM to hematologists. External validation has never been conducted. This study aims to externally validate the performance of the MM-BM DDx model. Patients and Methods: This multi-center external validation study was conducted using retrospective data of patients over 45 years old diagnosed with MM or BM at six university-affiliated hospitals in Thailand from 2016 to 2022. The MM-BM DDx development dataset, including patients from 2012 to 2015, was utilized during external validation. Diagnostic indicators for MM included in the MM-BM DDx model are serum creatinine, serum globulin, and serum alkaline phosphatase (ALP). MM and BM diagnosis was based on the documented International Classification of Diseases 10th Revision codes. Model performance was evaluated in terms of discrimination, calibration, and accuracy. Results: A total of 3018 patients were included in the validation dataset (586 with MM and 2432 with BM). Clinical characteristics were similar between the validation and development datasets. The MM-BM DDx model's predictions showed an AUC of 0.89 (95% CI, 0.87, 0.90). The predicted probabilities of MM from the model increased concordantly with the observed proportion of MM within the validation dataset. The estimated sensitivity, specificity, and LR for each odds class in the validation dataset were similar to those of the development dataset. Conclusion: The discriminative ability and calibration of the MM-BM DDx model were found to be preserved during external validation. These findings provide support for the practical use of the MM-BM DDx model to assist clinicians in identifying patients with destructive bone lesions who are likely to have MM and enable them to arrange timely referrals for further evaluation by hematologists.

The Survival Outcomes, Prognostic Factors and Adverse Events following Systemic Chemotherapy Treatment in Bone Sarcomas: A Retrospective Observational Study from the Experience of the Cancer Referral Center in Northern Thailand.

This study aimed to assess survival outcomes, prognostic factors, and adverse events following chemotherapy treatment for osteosarcoma and Ewing's sarcoma. This retrospective observational study was conducted to collect the data of the patients with osteosarcoma or Ewing's sarcoma who received chemotherapy treatment between 2008 and 2019. The flexible parametric survival model was performed to explore the adjusted survival probability and the prognostic factors. A total of 102 patients (79 with osteosarcoma and 23 with Ewing's sarcoma) were included. The estimated 5-year disease-free survival (DFS) and 5-year overall survival (OS) probabilities in patients with resectable disease were 60.9% and 63.3% for osteosarcoma, and 54.4% and 88.3% for Ewing's sarcoma, respectively, whereas the 5-year DFS and 5-year OS for those with unresectable/metastatic disease remained below 25%. Two prognostic factors for osteosarcoma included a response to neoadjuvant chemotherapy and female gender. Ewing's sarcoma patients aged 25 years and older were significantly associated with poorer survival outcomes. Of 181 chemotherapy treatment cycles, common self-reported adverse symptoms included tumor pain (n = 32, 17.7%), fever (n = 21, 11.6%), and fatigue (n = 16, 8.8%), while common grade III adverse events included febrile neutropenia (n = 13, 7.3%) and neutropenia (n = 9, 5.1%). There was no chemotherapy-related mortality (grade V) or anaphylaxis events.

The Role of Proteomics and Phosphoproteomics in the Discovery of Therapeutic Targets and Biomarkers in Acquired EGFR-TKI-Resistant Non-Small Cell Lung Cancer.

The discovery of potent EGFR-tyrosine kinase inhibitors (EGFR-TKIs) has revolutionized the treatment of EGFR-mutated lung cancer. Despite the fact that EGFR-TKIs have yielded several significant benefits for lung cancer patients, the emergence of resistance to EGFR-TKIs has been a substantial impediment to improving treatment outcomes. Understanding the molecular mechanisms underlying resistance is crucial for the development of new treatments and biomarkers for disease progression. Together with the advancement in proteome and phosphoproteome analysis, a diverse set of key signaling pathways have been successfully identified that provide insight for the discovery of possible therapeutically targeted proteins. In this review, we highlight the proteome and phosphoproteomic analyses of non-small cell lung cancer (NSCLC) as well as the proteome analysis of biofluid specimens that associate with acquired resistance in response to different generations of EGFR-TKI. Furthermore, we present an overview of the targeted proteins and potential drugs that have been tested in clinical studies and discuss the challenges of implementing this discovery in future NSCLC treatment.

Genomics-Driven Precision Medicine in Pediatric Solid Tumors.

Over the past decades, several study programs have conducted genetic testing in cancer patients to identify potential genetic targets for the development of precision therapeutic strategies. These biomarker-driven trials have demonstrated improved clinical outcomes and progression-free survival rates in various types of cancers, especially for adult malignancies. However, similar progress in pediatric cancers has been slow due to their distinguished mutation profiles compared to adults and the low frequency of recurrent genomic alterations. Recently, increased efforts to develop precision medicine for childhood malignancies have led to the identification of genomic alterations and transcriptomic profiles of pediatric patients which presents promising opportunities to study rare and difficult-to-access neoplasms. This review summarizes the current state of known and potential genetic markers for pediatric solid tumors and provides perspectives on precise therapeutic strategies that warrant further investigations.

Anti-arthritis Effects of Zingiberaceae Extracts on Models of Inflammatory Joint Disease.

Due to this becoming an aging society, the number of arthritis cases has been increasing. Unfortunately, some currently available medications can cause adverse effects. Using herbal remedies as a form of alternative medicine is becoming increasingly popular. Zingiber officinale (ZO), Curcuma longa (CL), and Kaempferia parviflora (KP) are herbal plants in the Zingiberaceae family that have potent anti-inflammatory effects. This study investigates the anti-inflammatory and chondroprotective effects of ZO, CL, and KP extracts on in vitro and ex vivo inflammatory models. The combinatorial anti-arthritis effect of each extract is also evaluated in an in vivo model. ZO extract preserves cartilaginous proteoglycans in proinflammatory cytokines-induced porcine cartilage explant in a fashion similar to that of CL and KP extracts and suppresses the expression of major inflammatory mediators in SW982 cells, particularly the COX2 gene. CL extract downregulates some inflammatory mediators and genes-associated cartilage degradation. Only KP extract shows a significant reduction in S-GAGs release in a cartilage explant model compared to the positive control, diacerein. In SW982 cells, it strongly suppresses many inflammatory mediators. The active constituents of each extract selectively downregulate inflammatory genes. The combined extracts show a reduction in inflammatory mediators to a similar degree as the combined active constituents. Reductions in paw swelling, synovial vascularity, inflammatory cell infiltration, and synovial hyperplasia are found in the combined extracts-treated arthritic rats. This study demonstrates that a combination of ZO, CL, and KP extracts has an anti-arthritis effect and could potentially be developed into an anti-arthritis cocktail for arthritis treatment.

Characterization of Cell-Free DNA Size Distribution in Osteosarcoma Patients.

PURPOSE: Cell-free DNA (cfDNA) analysis is a powerful tool for noninvasively predicting patient outcomes. We analyzed the size distribution of cfDNA and assessed its prognostic and diagnostic values in an osteosarcoma cohort. EXPERIMENTAL DESIGN: The fragment size distribution and level of cfDNA were analyzed in 15 healthy donors and 50 patients with osteosarcoma using automated capillary electrophoresis. The prognostic performance of cfDNA size analysis was assessed using univariate and multivariable analyses. By performing whole-genome sequencing of matched cfDNA and osteosarcoma tissue samples, we investigated the correlation between the size and mutation profiles of cfDNA and the mutation concordance between cfDNA and paired tissue tumors. RESULTS: The size of cfDNA fragments in patients with osteosarcoma was significantly shorter than in healthy donors, with the integrative analysis of size distribution and level of cfDNA achieving a high specificity and sensitivity of 100%. The short cfDNA fragment (150-bp cut-off) was an independent prognostic predictor in this osteosarcoma cohort [HR, 9.03; 95% confidence interval (CI), 1.13-72.20; P = 0.038]. Shortened cfDNA fragments were found to be a major source of mutations. Enrichment of cfDNA fragments with less than or equal to 150 bp by in silico size selection remarkedly improved the detection of copy-number variation signals up to 2.3-fold when compared with total cfDNA, with a higher concordance rate with matched osteosarcoma tissue. CONCLUSIONS: This finding demonstrated the potential of cfDNA size profiling in the stratification of poor prognostic patients with osteosarcoma. The short fragments of cfDNA are a promising source for boosting the detection of significant mutations in osteosarcoma. See related commentary by Weiser et al., p. 2017.

Potential target identification for osteosarcoma treatment: Gene expression re-analysis and drug repurposing.

Survival rate of osteosarcoma has remained plateaued for the past three decades. New treatment is needed to improve survival rate. Drug repurposing, a method to identify new indications of previous drugs, which saves time and cost compared to the de novo drug discovery. Data mining from gene expression profile was carried out and new potential targets were identified by using drug repurposing strategy. Selected data were newly categorized as pathophysiology and metastasis groups. Data were normalized and calculated the differential gene expression. Genes with log fold change ≥ 2 and adjusted p-value ≤ 0.05 were selected as primary candidate genes (PCGs). PCGs were further enriched to determine the secondary candidate genes (SCGs) by protein interaction analysis, upstream transcription factor and related-protein kinase identification. PCGs and SCGs were further matched with gene targeted of corresponding drugs from the Drug Repurposing Hub. A total of 778 targets were identified (360 from PCGs, and 418 from SCGs). This newly identified KLHL13 is a new candidate target based on its molecular function. KLHL13 was upregulated in clinical samples. We found 256 drugs from matching processes (50anti-cancerand206non-anticancerdrugs). Clinical trials of anti-cancer drugs from 5 targets (CDK4, BCL-2, JUN, SRC, PIK3CA) are being performed for osteosarcoma treatment. Niclosamide and synthetic PPARÉ£ ligands are candidates for repurposing due to the possibility based on their mechanism and pharmacology properties. Re-analysis of gene expression profile could identify new potential targets, confirm a current implication, and expand the chance of repurposing drugs for osteosarcoma treatment.

Performance of the Matsumiya scoring system in cervical cancer patients with bone metastasis: an external validation study.

BACKGROUND: Accurate prognostic prediction of survival in cervical cancer patients with bone metastasis is important for treatment planning. We aimed to externally validate the Matsumiya scoring system using external patient data. METHODS: We collected a retrospective cohort of patients with cervical cancer diagnosed with bone metastasis at Chiang Mai University Hospital from 1st January 2007 to 31st December 2016. The Matsumiya score was composed of 5 predictors, including the presence of extraskeletal metastasis, ECOG performance status, history of previous chemo- or radiotherapy, the presence of multiple bone metastasis, and bone metastasis-free interval < 12 months. Harrell's C-statistics and score calibration plots were used to evaluate the score performance. We also reconstructed the development study to estimate apparent performance values for comparison during external validation. RESULTS: A total of 124 cervical cancer patients with bone metastasis were included in this study. The 13-, 26-, and 52-week survival probabilities in the validation study were 70.1%, 50.5%, and 25.7%, respectively. Several differences were identified between development and validation studies regarding clinical characteristics, case-mix, and predictor-outcome associations. Harrell's C-statistics in the development and validation study were 0.714 and 0.567. The score showed poor agreement between the observed and the predicted survival probabilities in the validation study. Score reweighting and refitting showed only modest improvement in performance. CONCLUSION: A prognostic scoring system by Matsumiya et al. performed poorly in our cohort of Thai cervical cancer patients with bone metastasis. We suggested that the score should be sufficiently updated before being used.

Mass Spectrometric-Based Proteomics for Biomarker Discovery in Osteosarcoma: Current Status and Future Direction.

Due to a lack of novel therapies and biomarkers, the clinical outcomes of osteosarcoma patients have not significantly improved for decades. The advancement of mass spectrometry (MS), peptide quantification, and downstream pathway analysis enables the investigation of protein profiles across a wide range of input materials, from cell culture to long-term archived clinical specimens. This can provide insight into osteosarcoma biology and identify candidate biomarkers for diagnosis, prognosis, and stratification of chemotherapy response. In this review, we provide an overview of proteomics studies of osteosarcoma, indicate potential biomarkers that might be promising therapeutic targets, and discuss the challenges and opportunities of mass spectrometric-based proteomics in future osteosarcoma research.

Descriptive epidemiology of soft tissue sarcomas and gastrointestinal stromal tumors in Thailand.

This study aimed to analyze burden of STS and GIST in population and survival rate which represented the current situation of treatment in Thailand. The data was collected from five population-based cancer registries around the country for the period 2001 through 2015. The Segi world standard population was used to calculated age-standardized incidence rates (ASR). Standardized rate ratios (SRR) were used to compare populations. Joinpoint Trend Analysis was used to assess changes in incidence. STATA was used to examine patient survival rates. During the study period, 4080 cases of STS and 457 cases of GIST were reported. The ASR of STS and GIST was 2.14/100,000 person-years and 0.22/100,000 person-years, respectively. The most common histological types of STS were unspecified sarcoma (24.8%), leiomyosarcoma (19.0%) and liposarcoma (11.4%). The overall ASR of STS in Thailand was relatively low compared to Western countries. The five-year survival rate was 62.6% for STS and 63.4% for GIST, which was comparable to the rates reported in other countries. This is the first report of STS and GIST from PBCRs in Thailand. Based on current healthcare service, an overall survival rates of STS and GIST are comparable to those reported from others.

Clinical Implication of Circulating Tumor Cells Expressing Epithelial Mesenchymal Transition (EMT) and Cancer Stem Cell (CSC) Markers and Their Perspective in HCC: A Systematic Review.

Circulating tumor cells (CTCs) play a key role in hematogenous metastasis and post-surgery recurrence. In hepatocellular carcinoma (HCC), CTCs have emerged as a valuable source of therapeutically relevant information. Certain subsets or phenotypes of CTCs can survive in the bloodstream and induce metastasis. Here, we performed a systematic review on the importance of epithelial-mesenchymal transition (EMT)-CTCs and circulating cancer stem cells (CCSCs) in metastatic processes and their prognostic power in HCC management. PubMed, Scopus, and Embase databases were searched for relevant publications. PRISMA criteria were used to review all studies. Twenty publications were eligible, of which 14, 5, and 1 study reported EMT-CTCs, CCSCs, and both phenotypes, respectively. Most studies evaluated that mesenchymal CTCs and CCSCs positivity were statistically associated with extensive clinicopathological features, including larger size and multiple numbers of tumors, advanced stages, micro/macrovascular invasion, and metastatic/recurrent disease. A preliminary meta-analysis showed that the presence of mesenchymal CTCs in pre- and postoperative blood significantly increased the risk of early recurrence. Mesenchymal-CTCs positivity was the most reported association with inferior outcomes based on the prognosis of HCC recurrence. Our finding could be a step forward, conveying additional prognostic values of CTC subtypes as promising biomarkers in HCC management.

Osteosarcoma-Specific Genes as a Diagnostic Tool and Clinical Predictor of Tumor Progression.

A liquid biopsy is currently an interesting tool for measuring tumor material with the advantage of being non-invasive. The overexpression of vimentin and ezrin genes was associated with epithelial-mesenchymal transition (EMT), a key process in metastasis and progression in osteosarcoma (OS). In this study, we identified other OS-specific genes by calculating differential gene expression using the Gene Expression Omnibus (GEO) database, confirmed by using quantitative reverse transcription-PCR (qRT-PCR) to detect OS-specific genes, including VIM and ezrin in the buffy coat, which were obtained from the whole blood of OS patients and healthy donors. Furthermore, the diagnostic model for OS detection was generated by utilizing binary logistic regression with a multivariable fractional polynomial (MFP) algorithm. The model incorporating VIM, ezrin, and COL5A2 genes exhibited outstanding discriminative ability, as determined by the receiver operating characteristic curve (AUC = 0.9805, 95% CI 0.9603, 1.000). At the probability cut-off value of 0.3366, the sensitivity and the specificity of the model for detecting OS were 98.63% (95% CI 90.5, 99.7) and 94.94% (95% CI 87.5, 98.6), respectively. Bioinformatic analysis and qRT-PCR, in our study, identified three candidate genes that are potential diagnostic and prognostic genes for OS.