Genetic heterogeneity and cancer drug resistance

Monitoring changing patterns in HER2 addiction by liquid biopsy in advanced breast cancer patients

BACKGROUND

During targeted treatment, HER2-positive breast cancers invariably lose HER2 DNA amplification. In contrast, and interestingly, HER2 proteins may be either lost or gained. To longitudinally and systematically appreciate complex/discordant changes in HER2 DNA/protein stoichiometry, HER2 DNA copy numbers and soluble blood proteins (aHER2/sHER2) were tested in parallel, non-invasively (by liquid biopsy), and in two-dimensions, hence HER2-2D.

METHODS

aHER2 and sHER2 were assessed by digital PCR and ELISA before and after standard-of-care treatment of advanced HER2-positive breast cancer patients (n=37) with the antibody-drug conjugate (ADC) Trastuzumab-emtansine (T-DM1).

RESULTS

As expected, aHER2 was invariably suppressed by T-DM1, but this loss was surprisingly mirrored by sHER2 gain, sometimes of considerable entity, in most (30/37; 81%) patients. This unorthodox split in HER2 oncogenic dosage was supported by reciprocal aHER2/sHER2 kinetics in two representative cases, and an immunohistochemistry-high status despite copy-number-neutrality in 4/5 available post-T-DM1 tumor re-biopsies from sHER2-gain patients. Moreover, sHER2 was preferentially released by dying breast cancer cell lines treated in vitro by T-DM1. Finally, sHER2 gain was associated with a longer PFS than sHER2 loss (mean PFS 282 vs 133 days, 95% CI [210-354] vs [56-209], log-rank test p=0.047), particularly when cases (n=11) developing circulating HER2-bypass alterations during T-DM1 treatment were excluded (mean PFS 349 vs 139 days, 95% CI [255-444] vs [45-232], log-rank test p=0.009).

CONCLUSIONS

HER2 gain is adaptively selected in tumor tissues and recapitulated in blood by sHER2 gain. Possibly, an increased oncogenic dosage is beneficial to the tumor during anti-HER2 treatment with naked antibodies, but favorable to the host during treatment with a strongly cytotoxic ADC such as T-DM1. In the latter case, HER2-gain tumors may be kept transiently in check until alternative oncogenic drivers, revealed by liquid biopsy, bypass HER2. Whichever the interpretation, HER2-2D might help to tailor/prioritize anti-HER2 treatments, particularly ADCs active on aHER2-low/sHER2-low tumors.

TRIAL REGISTRATION

NCT05735392 retrospectively registered on January 31, 2023 https://www.

CLINICALTRIALS

gov/search?term=NCT05735392.

Advancing cancer drug development with mechanistic mathematical modeling: bridging the gap between theory and practice

Quantitative predictive modeling of cancer growth, progression, and individual response to therapy is a rapidly growing field. Researchers from mathematical modeling, systems biology, pharmaceutical industry, and regulatory bodies, are collaboratively working on predictive models that could be applied for drug development and, ultimately, the clinical management of cancer patients. A plethora of modeling paradigms and approaches have emerged, making it challenging to compile a comprehensive review across all subdisciplines. It is therefore critical to gauge fundamental design aspects against requirements, and weigh opportunities and limitations of the different model types. In this review, we discuss three fundamental types of cancer models: space-structured models, ecological models, and immune system focused models. For each type, it is our goal to illustrate which mechanisms contribute to variability and heterogeneity in cancer growth and response, so that the appropriate architecture and complexity of a new model becomes clearer. We present the main features addressed by each of the three exemplary modeling types through a subjective collection of literature and illustrative exercises to facilitate inspiration and exchange, with a focus on providing a didactic rather than exhaustive overview. We close by imagining a future multi-scale model design to impact critical decisions in oncology drug development.

Unveiling Alterations of Epigenetic Modifications and Chromatin Architecture Leading to Lipid Metabolic Reprogramming during the Evolutionary Trastuzumab Adaptation of HER2-Positive Breast Cancer

Secondary trastuzumab resistance represents an evolutionary adaptation of HER2-positive breast cancer during anti-HER2 treatment. Most current studies have tended to prioritize HER2 and its associated signaling pathways, often overlooking broader but seemingly less relevant cellular processes, along with their associated genetic and epigenetic mechanisms. Here, transcriptome data is not only characterized but also examined epigenomic and 3D genome architecture information in both trastuzumab-sensitive and secondary-resistant breast cancer cells. The findings reveal that the global metabolic reprogramming associated with trastuzumab resistance may stem from genome-wide alterations in both histone modifications and chromatin structure. Specifically, the transcriptional activities of key genes involved in lipid metabolism appear to be regulated by variant promoter H3K27me3 and H3K4me3 modifications, as well as promoter-enhancer interactions. These discoveries offer valuable insights into how cancer cells adapt to anti-tumor drugs and have the potential to impact future diagnostic and treatment strategies.

Cell Electrokinetic Fingerprint: A Novel Approach Based on Optically Induced Dielectrophoresis (ODEP) for In-Flow Identification of Single Cells

A novel optically induced dielectrophoresis (ODEP) system that can operate under flow conditions is designed for automatic trapping of cells and subsequent induction of 2D multi-frequency cell trajectories. Like in a "ping-pong" match, two virtual electrode barriers operate in an alternate mode with varying frequencies of the input voltage. The so-derived cell motions are characterized via time-lapse microscopy, cell tracking, and state-of-the-art machine learning algorithms, like the wavelet scattering transform (WST). As a cell-electrokinetic fingerprint, the dynamic of variation of the cell displacements happening, over time, is quantified in response to different frequency values of the induced electric field. When tested on two biological scenarios in the cancer domain, the proposed approach discriminates cellular dielectric phenotypes obtained, respectively, at different early phases of drug-induced apoptosis in prostate cancer (PC3) cells and for differential expression of the lectine-like oxidized low-density lipoprotein receptor-1 (LOX-1) transcript levels in human colorectal adenocarcinoma (DLD-1) cells. The results demonstrate increased discrimination of the proposed system and pose an additional basis for making ODEP-based assays addressing cancer heterogeneity for precision medicine and pharmacological research.

Mechanisms of drug resistance in HCC

HCC comprises ∼80% of primary liver cancer. HCC is the only major cancer for which death rates have not improved over the last 10 years. Most patients are diagnosed with advanced disease when surgical and locoregional treatments are not feasible or effective. Sorafenib, a multikinase inhibitor targeting cell growth and angiogenesis, was approved for advanced unresectable HCC in 2007. Since then, other multikinase inhibitors have been approved. Lenvatinib was found to be noninferior to sorafenib as a first-line agent. Regorafenib, cabozantinib, and ramucirumab were shown to prolong survival as second-line agents. Advances in immunotherapy for HCC have also added hope for patients, but their efficacy remains limited. A large proportion of patients with advanced HCC gain no long-term benefit from systemic therapy due to primary and acquired drug resistance, which, combined with its rising incidence, keeps HCC a highly fatal disease. This review summarizes mechanisms of primary and acquired resistance to therapy and includes methods for bypassing resistance. It addresses recent advancements in immunotherapy, provides new perspectives on the linkage between drug resistance and molecular etiology of HCC, and evaluates the role of the microbiome in drug resistance. It also discusses alterations in signaling pathways, dysregulation of apoptosis, modulations in the tumor microenvironment, involvement of cancer stem cells, changes in drug metabolism/transport, tumor hypoxia, DNA repair, and the role of microRNAs in drug resistance. Understanding the interplay among these factors will provide guidance on the development of new therapeutic strategies capable of improving patient outcomes.

Overcoming drug resistance with specific nano scales to targeted therapy: Focused on metastatic cancers

Metastatic cancer, which accounts for the majority of cancer fatalities, is a difficult illness to treat. Currently used cancer treatments include radiation therapy, chemotherapy, surgery, and targeted treatment (immune, gene, and hormonal). The disadvantages of these treatments include a high risk of tumor recurrence and surgical complications that may result in permanent deformities. On the other hand, most chemotherapy drugs are small molecules, which usually have unfavorable side effects, low absorption, poor selectivity, and multi-drug resistance. Anticancer drugs can be delivered precisely to the cancer spot by encapsulating them to reduce side effects. Stimuli-responsive nanocarriers can be used for drug release at cancer sites and provide target-specific delivery. As previously stated, metastasis is the primary cause of cancer-related mortality. We have evaluated the usage of nano-medications in the treatment of some metastatic tumors.

Measured Steps: Navigating the Path of Oligoprogressive Lung Cancer with Targeted and Immunotherapies

PURPOSE OF REVIEW

This review discusses the definitions, treatment modalities, management, future directions, and ongoing clinical trials of oligoprogressive disease in oncogene-driven and non-oncogene-driven NSCLC.

RECENT FINDINGS

During the last decades, diagnostic and treatment modalities for oligometastatic NSCLC have advanced significantly, leading to improved survival. Additionally, our understanding of the tumor biology of oligoprogressive disease has expanded. However, despite the efforts of organizations, such as EORTC, ESTRO, and ASTRO proposing definitions for oligometastatic and oligoprogressive disease, heterogeneity in definitions persists in (ongoing) trials. Recognizing the significance of subclassification within oligoprogressive disease in NSCLC and the varying risks associated with subsequent metastatic spread, there is a call for tailored management strategies. A consensus on standardized criteria for the definition of oligoprogressive disease is urgently needed and will not only facilitate meaningful comparisons between studies but also pave the way for the development of personalized treatment plans that take into account the heterogeneous nature of oligoprogressive disease.

Successful treatment of severe lung cancer caused by third-generation EGFR-TKI resistance due to EGFR genotype conversion with afatinib plus anlotinib

Third-generation EGFR-TKIs can be used to treat advanced non-small cell lung cancer patients with T790M resistance mutation induced by first- or second-generation EGFR-TKIs. However, it will also result in drug resistance, and the resistance mechanisms of third-generation EGFR-TKIs are complex. Here we reported a patient diagnosed with advanced lung adenocarcinoma and EGFR positive in September 2016. Following first-line targeted therapy with gefitinib, genetic testing showed EGFR T790M positive, which resulted in a change to osimertinib targeted therapy. In May 2021, troponin and creatinine levels were elevated, and the tumor hyperprogressed to severe lung cancer. Repeated genetic testing revealed that EGFR genotype converted to a non-classical mutation and EGFR T790M turned negative, which caused third-generation EGFR-TKI resistance. As a result, afatinib combined with anlotinib was selected to stabilize the patient's condition. We were inspired by the case that it reflects the significance and necessity of exploring the resistance mechanism and dynamically detecting genetic status throughout the course of treatment, which may help realize individualized precision therapy, and maximize the potential of patient.

Phytochemical-Based Nanomedicine for Targeting Tumor Microenvironment and Inhibiting Cancer Chemoresistance: Recent Advances and Pharmacological Insights

Cancer remains the leading cause of death and rapidly evolving disease worldwide. The understanding of disease pathophysiology has improved through advanced research investigation, and several therapeutic strategies are being used for better cancer treatment. However, the increase in cancer relapse and metastatic-related deaths indicate that available therapies and clinically approved chemotherapy drugs are not sufficient to combat cancer. Further, the constant crosstalk between tumor cells and the tumor microenvironment (TME) is crucial for the development, progression, metastasis, and therapeutic response to tumors. In this regard, phytochemicals with multimodal targeting abilities can be used as an alternative to current cancer therapy by inhibiting cancer survival pathways or modulating TME. However, due to their poor pharmacokinetics and low bioavailability, the success of phytochemicals in clinical trials is limited. Therefore, developing phytochemical-based nanomedicine or phytonanomedicine can improve the pharmacokinetic profile of these phytochemicals. Herein, the molecular characteristics and pharmacological insights of the proposed phytonanomedicine in cancer therapy targeting tumor tissue and altering the characteristics of cancer stem cells, chemoresistance, TME, and cancer immunity are well discussed. Further, we have highlighted the clinical perspective and challenges of phytonanomedicine in filling the gap in potential cancer therapeutics using various nanoplatforms. Overall, we have discussed how clinical success and pharmacological insights could make it more beneficial to boost the concept of nanomedicine in the academic and pharmaceutical fields to counter cancer metastases and drug resistance.

Mutation divergence over space in tumour expansion

Mutation accumulation in tumour evolution is one major cause of intra-tumour heterogeneity (ITH), which often leads to drug resistance during treatment. Previous studies with multi-region sequencing have shown that mutation divergence among samples within the patient is common, and the importance of spatial sampling to obtain a complete picture in tumour measurements. However, quantitative comparisons of the relationship between mutation heterogeneity and tumour expansion modes, sampling distances as well as the sampling methods are still few. Here, we investigate how mutations diverge over space by varying the sampling distance and tumour expansion modes using individual-based simulations. We measure ITH by the Jaccard index between samples and quantify how ITH increases with sampling distance, the pattern of which holds in various sampling methods and sizes. We also compare the inferred mutation rates based on the distributions of variant allele frequencies under different tumour expansion modes and sampling sizes. In exponentially fast expanding tumours, a mutation rate can always be inferred for any sampling size. However, the accuracy compared with the true value decreases when the sampling size decreases, where small sampling sizes result in a high estimate of the mutation rate. In addition, such an inference becomes unreliable when the tumour expansion is slow, such as in surface growth.

Unveiling the novel immune and molecular signatures of ovarian cancer: insights and innovations from single-cell sequencing

Ovarian cancer is a highly heterogeneous and lethal malignancy with limited treatment options. Over the past decade, single-cell sequencing has emerged as an advanced biological technology capable of decoding the landscape of ovarian cancer at the single-cell resolution. It operates at the level of genes, transcriptomes, proteins, epigenomes, and metabolisms, providing detailed information that is distinct from bulk sequencing methods, which only offer average data for specific lesions. Single-cell sequencing technology provides detailed insights into the immune and molecular mechanisms underlying tumor occurrence, development, drug resistance, and immune escape. These insights can guide the development of innovative diagnostic markers, therapeutic strategies, and prognostic indicators. Overall, this review provides a comprehensive summary of the diverse applications of single-cell sequencing in ovarian cancer. It encompasses the identification and characterization of novel cell subpopulations, the elucidation of tumor heterogeneity, the investigation of the tumor microenvironment, the analysis of mechanisms underlying metastasis, and the integration of innovative approaches such as organoid models and multi-omics analysis.

Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and therapeutic targets

Intratumor heterogeneity (ITH) profoundly affects therapeutic responses and clinical outcomes. However, the widespread methods for assessing ITH based on genomic sequencing or pathological slides, which rely on limited tissue samples, may lead to inaccuracies due to potential sampling biases. Using a newly established multicenter breast cancer radio-multiomic dataset (n = 1474) encompassing radiomic features extracted from dynamic contrast-enhanced magnetic resonance images, we formulated a noninvasive radiomics methodology to effectively investigate ITH. Imaging ITH (IITH) was associated with genomic and pathological ITH, predicting poor prognosis independently in breast cancer. Through multiomic analysis, we identified activated oncogenic pathways and metabolic dysregulation in high-IITH tumors. Integrated metabolomic and transcriptomic analyses highlighted ferroptosis as a vulnerability and potential therapeutic target of high-IITH tumors. Collectively, this work emphasizes the superiority of radiomics in capturing ITH. Furthermore, we provide insights into the biological basis of IITH and propose therapeutic targets for breast cancers with elevated IITH.

Electrical Characterization and Analysis of Single Cells and Related Applications

Biological parameters extracted from electrical signals from various body parts have been used for many years to analyze the human body and its behavior. In addition, electrical signals from cancer cell lines, normal cells, and viruses, among others, have been widely used for the detection of various diseases. Single-cell parameters such as cell and cytoplasmic conductivity, relaxation frequency, and membrane capacitance are important. There are many techniques available to characterize biomaterials, such as nanotechnology, microstrip cavity resonance measurement, etc. This article reviews single-cell isolation and sorting techniques, such as the micropipette separation method, separation and sorting system (dual electrophoretic array system), DEPArray sorting system (dielectrophoretic array system), cell selector sorting system, and microfluidic and valve devices, and discusses their respective advantages and disadvantages. Furthermore, it summarizes common single-cell electrical manipulations, such as single-cell amperometry (SCA), electrical impedance sensing (EIS), impedance flow cytometry (IFC), cell-based electrical impedance (CEI), microelectromechanical systems (MEMS), and integrated microelectrode array (IMA). The article also enumerates the application and significance of single-cell electrochemical analysis from the perspectives of CTC liquid biopsy, recombinant adenovirus, tumor cells like lung cancer DTCs (LC-DTCs), and single-cell metabolomics analysis. The paper concludes with a discussion of the current limitations faced by single-cell analysis techniques along with future directions and potential application scenarios.

Archival single-cell genomics reveals persistent subclones during DCIS progression

Ductal carcinoma in situ (DCIS) is a common precursor of invasive breast cancer. Our understanding of its genomic progression to recurrent disease remains poor, partly due to challenges associated with the genomic profiling of formalin-fixed paraffin-embedded (FFPE) materials. Here, we developed Arc-well, a high-throughput single-cell DNA-sequencing method that is compatible with FFPE materials. We validated our method by profiling 40,330 single cells from cell lines, a frozen tissue, and 27 FFPE samples from breast, lung, and prostate tumors stored for 3-31 years. Analysis of 10 patients with matched DCIS and cancers that recurred 2-16 years later show that many primary DCIS had already undergone whole-genome doubling and clonal diversification and that they shared genomic lineages with persistent subclones in the recurrences. Evolutionary analysis suggests that most DCIS cases in our cohort underwent an evolutionary bottleneck, and further identified chromosome aberrations in the persistent subclones that were associated with recurrence.

Viscum album Induces Apoptosis by Regulating STAT3 Signaling Pathway in Breast Cancer Cells

In this study, we investigated the potential anticancer effects of Viscum album, a parasitic plant that grows on Malus domestica (VaM) on breast cancer cells, and explored the underlying mechanisms. VaM significantly inhibited cell viability and proliferation and induced apoptosis in a dose-dependent manner. VaM also regulated cell cycle progression and effectively inhibited activation of the STAT3 signaling pathway through SHP-1. Combining VaM with low-dose doxorubicin produced a synergistic effect, highlighting its potential as a promising therapeutic. In vivo, VaM administration inhibited tumor growth and modulated key molecular markers associated with breast cancer progression. Overall, our findings provide strong evidence for the therapeutic potential of VaM in breast cancer treatment and support further studies exploring clinical applications.

Angiogenic signaling pathways and anti-angiogenic therapy for cancer

Angiogenesis, the formation of new blood vessels, is a complex and dynamic process regulated by various pro- and anti-angiogenic molecules, which plays a crucial role in tumor growth, invasion, and metastasis. With the advances in molecular and cellular biology, various biomolecules such as growth factors, chemokines, and adhesion factors involved in tumor angiogenesis has gradually been elucidated. Targeted therapeutic research based on these molecules has driven anti-angiogenic treatment to become a promising strategy in anti-tumor therapy. The most widely used anti-angiogenic agents include monoclonal antibodies and tyrosine kinase inhibitors (TKIs) targeting vascular endothelial growth factor (VEGF) pathway. However, the clinical benefit of this modality has still been limited due to several defects such as adverse events, acquired drug resistance, tumor recurrence, and lack of validated biomarkers, which impel further research on mechanisms of tumor angiogenesis, the development of multiple drugs and the combination therapy to figure out how to improve the therapeutic efficacy. Here, we broadly summarize various signaling pathways in tumor angiogenesis and discuss the development and current challenges of anti-angiogenic therapy. We also propose several new promising approaches to improve anti-angiogenic efficacy and provide a perspective for the development and research of anti-angiogenic therapy.

Applying single cell multi-omic analyses to understand treatment resistance in pediatric high grade glioma

Despite improvements in cancer patient outcomes seen in the past decade, tumor resistance to therapy remains a major impediment to achieving durable clinical responses. Intratumoral heterogeneity related to genetic, epigenetic, transcriptomic, proteomic, and metabolic differences between individual cancer cells has emerged as a driver of therapeutic resistance. This cell to cell heterogeneity can be assessed using single cell profiling technologies that enable the identification of tumor cell clones that exhibit similar defining features like specific mutations or patterns of DNA methylation. Single cell profiling of tumors before and after treatment can generate new insights into the cancer cell characteristics that confer therapeutic resistance by identifying intrinsically resistant sub-populations that survive treatment and by describing new cellular features that emerge post-treatment due to tumor cell evolution. Integrative, single cell analytical approaches have already proven advantageous in studies characterizing treatment-resistant clones in cancers where pre- and post-treatment patient samples are readily available, such as leukemia. In contrast, little is known about other cancer subtypes like pediatric high grade glioma, a class of heterogeneous, malignant brain tumors in children that rapidly develop resistance to multiple therapeutic modalities, including chemotherapy, immunotherapy, and radiation. Leveraging single cell multi-omic technologies to analyze naïve and therapy-resistant glioma may lead to the discovery of novel strategies to overcome treatment resistance in brain tumors with dismal clinical outcomes. In this review, we explore the potential for single cell multi-omic analyses to reveal mechanisms of glioma resistance to therapy and discuss opportunities to apply these approaches to improve long-term therapeutic response in pediatric high grade glioma and other brain tumors with limited treatment options.

Construction of multiple concentration gradients for single-cell level drug screening

Isolation and manipulation of single cells play a crucial role in drug screening. However, previously reported single-cell drug screening lacked multiple-dose concentration gradient studies, which limits their ability to predict drug performance accurately. To solve this problem, we constructed a multiconcentration gradient generator in which a Tai Chi-spiral mixer can accelerate solution mixing in a short time and produce a linear concentration gradient. Later, a gradient generator combined with a single-cell capture array was adopted to investigate the effects of single or combined doses of 5-fluorouracil and cisplatin on human hepatoma cells and human breast carcinoma cells (at the single-cell level). The results showed that both drugs were effective in inhibiting the growth of cancer cells, and the combination was more effective for human hepatoma cells. In addition, the relationship between the biomechanical heterogeneity (e.g., deformability and size) of tumor cells and potential drug resistance at the single-cell level was investigated, indicating that small and/or deformable cells were more resistant than large and/or less deformable cells. The device provides a simple and reliable platform for studying the optimal dosage of different drug candidates at the single-cell level and effectively screening single-agent chemotherapy regimens and combination therapies.

cRGD-targeted heparin nanoparticles for effective dual drug treatment of cisplatin-resistant ovarian cancer

Resistance to the chemotherapeutic agent cisplatin (DDP) is the primary reason for invalid chemotherapy of ovarian cancer. Given the complex mechanisms underlying chemo-resistance, the design of combination therapies based on blocking multiple mechanisms is a rationale to synergistically elevate therapeutic effect for effectively overcoming cancer chemo-resistance. Herein, we demonstrated a multifunctional nanoparticle (DDP-Ola@HR), which could simultaneously co-deliver DDP and Olaparib (Ola, DNA damage repair inhibitor) using targeted ligand cRGD peptide modified with heparin (HR) as nanocarrier, enabling the concurrent tackling of multiple resistance mechanisms to effectively inhibit the growth and metastasis of DDP-resistant ovarian cancer. In combination strategy, heparin could suppress the function of multidrug resistance-associated protein 2 (MRP2) and P-glycoprotein (P-gp) to promote the intracellular accumulation of DDP and Ola by specifically binding with heparanase (HPSE) to down-regulate PI3K/AKT/mTOR signaling pathway, and simultaneously served as a carrier combined with Ola to synergistically enhance the anti-proliferation ability of DDP for resistant ovarian cancer, thus achieving great therapeutic efficacy. Our DDP-Ola@HR could provide a simple and multifunctional combination strategy to trigger an anticipated cascading effect, thus effectively overcoming the chemo-resistance of ovarian cancer.

Pathway-level mutation analysis in primary high-grade serous ovarian cancer and matched brain metastases

Brain metastases (BMs) in ovarian cancer (OC) are a rare event. BMs occur most frequently in high-grade serous (HGS) OC. The molecular features of BMs in HGSOC are poorly understood. We performed a whole-exome sequencing analysis of ten matched pairs of formalin-fixed paraffin-embedded samples from primary HGSOC and corresponding BMs. Enrichment significance (p value; false discovery rate) was computed using the Reactome, the Kyoto Encyclopedia of Genes and Genomes pathway collections, and the Gene Ontology Biological Processes. Germline DNA damage repair variants were found in seven cases (70%) and involved the BRCA1, BRCA2, ATM, RAD50, ERCC4, RPA1, MLHI, and ATR genes. Somatic mutations of TP53 were found in nine cases (90%) and were the only stable mutations between the primary tumor and BMs. Disturbed pathways in BMs versus primary HGSOC constituted a complex network and included the cell cycle, the degradation of the extracellular matrix, cell junction organization, nucleotide metabolism, lipid metabolism, the immune system, G-protein-coupled receptors, intracellular vesicular transport, and reaction to chemical stimuli (Golgi vesicle transport and olfactory signaling). Pathway analysis approaches allow for a more intuitive interpretation of the data as compared to considering single-gene aberrations and provide an opportunity to identify clinically informative alterations in HGSOC BM.

Impact of a haplotype (composed of the APC, KRAS, and TP53 genes) on colorectal adenocarcinoma differentiation and patient prognosis

BACKGROUND

Many types of gene mutation are associated with the drug resistance of cancer cells. XELOX is a new and efficient surgical adjuvant chemotherapy for colorectal adenocarcinoma. However, drug-resistant related genetic mutations associated with this treatment remain unknown.

METHODS

Next-generation sequencing (NGS) was performed on 36 colorectal cancer patients to identify mutations among patients with residual tumors following preoperative chemotherapy. Enrichment and prognosis of these mutations were evaluated in a TCGA cohort. The pathology of cases with poor prognosis-related mutations was also determined.

RESULTS

A sequence of SNPs associated with the APC, KRAS, and TP53 genes in 13 of 19 subjects with residual tumors after preoperative chemotherapy was identified. Using survival analysis data from 317 cases in the TCGA database, a prognosis-related haplotype composed of SNPs from APC, KRAS, and TP53 was assembled. Colorectal cancer patients with these mutations had a lower 5-year tumor-specific survival rate than those without (p < 0.05). Most patients with these mutations were at a higher clinical stage (III-IV) of disease. Enrolled subjects with the identified haplotype tended to have poor cancer cell differentiation.

CONCLUSIONS

The prognosis-related haplotype can be used as a marker of drug resistance and prognosis in colorectal cancer patients after preoperative chemotherapy.

CREAMMIST: an integrative probabilistic database for cancer drug response prediction

Extensive in vitro cancer drug screening datasets have enabled scientists to identify biomarkers and develop machine learning models for predicting drug sensitivity. While most advancements have focused on omics profiles, cancer drug sensitivity scores precalculated by the original sources are often used as-is, without consideration for variabilities between studies. It is well-known that significant inconsistencies exist between the drug sensitivity scores across datasets due to differences in experimental setups and preprocessing methods used to obtain the sensitivity scores. As a result, many studies opt to focus only on a single dataset, leading to underutilization of available data and a limited interpretation of cancer pharmacogenomics analysis. To overcome these caveats, we have developed CREAMMIST (https://creammist.mtms.dev), an integrative database that enables users to obtain an integrative dose-response curve, to capture uncertainty (or high certainty when multiple datasets well align) across five widely used cancer cell-line drug-response datasets. We utilized the Bayesian framework to systematically integrate all available dose-response values across datasets (>14 millions dose-response data points). CREAMMIST provides easy-to-use statistics derived from the integrative dose-response curves for various downstream analyses such as identifying biomarkers, selecting drug concentrations for experiments, and training robust machine learning models.

Molecular targeted therapy for anticancer treatment

Since the initial clinical approval in the late 1990s and remarkable anticancer effects for certain types of cancer, molecular targeted therapy utilizing small molecule agents or therapeutic monoclonal antibodies acting as signal transduction inhibitors has served as a fundamental backbone in precision medicine for cancer treatment. These approaches are now used clinically as first-line therapy for various types of human cancers. Compared to conventional chemotherapy, targeted therapeutic agents have efficient anticancer effects with fewer side effects. However, the emergence of drug resistance is a major drawback of molecular targeted therapy, and several strategies have been attempted to improve therapeutic efficacy by overcoming such resistance. Herein, we summarize current knowledge regarding several targeted therapeutic agents, including classification, a brief biology of target kinases, mechanisms of action, examples of clinically used targeted therapy, and perspectives for future development.

Publication trends and hotspots of drug resistance in colorectal cancer during 2002-2021: A bibliometric and visualized analysis

Background

Chemotherapy, radiotherapy, targeted therapy and immunotherapy have demonstrated expected clinical efficacy, while drug resistance remains the predominant limiting factor to therapeutic failure in patients with colorectal cancer (CRC). Although there have been numerous basic and clinical studies on CRC resistance in recent years, few publications utilized the bibliometric method to evaluate this field. The objective of current study was to provide a comprehensive analysis of the current state and changing trends of drug resistance in CRC over the past 20 years.

Methods

The Web of Science Core Collection (WOSCC) was utilized to extracted all studies regarding drug resistance in CRC during 2002-2021. CiteSpace and online platform of bibliometrics were used to evaluate the contributions of various countries/regions, institutions, authors and journals in this field. Moreover, the recent research hotspots and promising future trends were identified through keywords analysis by CiteSpace and VOSviewer.

Results

1451 related publications from 2002 to 2021 in total were identified and collected. The number of global publications in this field has increased annually. China and the USA occupied the top two places with respect to the number of publications, contributing more than 60% of global publications. Sun Yat-sen University and Oncotarget were the institution and journal which published the most papers, respectively. Bardelli A from Italy was the most prolific writer and had the highest H-index. Keywords burst analysis identified that “Growth factor receptor”, “induced apoptosis” and “panitumumab” were the ones with higher burst strength in the early stage of this field. Analysis of keyword emergence time showed that “oxaliplatin resistance”, “MicroRNA” and “epithelial mesenchymal transition (EMT)” were the keywords with later average appearing year (AAY).

Conclusions

The number of publications and research interest on drug resistance in CRC have been increasing annually. The USA and China were the main driver and professor Bardelli A was the most outstanding researcher in this field. Previous studies have mainly concentrated on growth factor receptor and induced apoptosis. Oxaliplatin resistance, microRNA and EMT as recently appeared frontiers of research that should be closely tracked in the future.

Reversal of Epithelial-Mesenchymal Transition and Inhibition of Tumor Stemness of Breast Cancer Cells Through Advanced Combined Chemotherapy

The abnormal activation of the Wnt/β-catenin signaling pathway and epithelial-mesenchymal transition (EMT) in drug-resistant tumor cells and cancer stem cells (CSCs) stimulate tumor metastasis and recurrence. Here, a promising combined chemotherapeutic strategy of salinomycin (SL) and doxorubicin (DOX) with specific inhibition of tumor stemness by a targeted co-delivery nanosystem was developed to overcome this abnormal progression. This strategy could be benefit drugs to effectively penetrate and infiltrate into spheres of 3D-cultured breast cancer stem cells (BCSCs). The expression of the Wnt/β-catenin signaling pathway-related genes (β-catenin, LRP6, LEF1, and TCF12) and target genes (Cyclin D1, Cmyc, and Fibronectin) as well as CSC stemness-related genes (Oct4, Nanog, and Hes1) was downregulated by redox-sensitive co-delivery micelles decorated with oligohyaluronic acid as the active targeting moiety. The changes in EMT-associated gene expression (E-cadherin and Vimentin) in vitro showed that the EMT process was also effectively inverted. This strategy achieved a strong inhibitory effect on solid tumor growth and an effective reduction in the risk of tumor metastasis in 4T1 tumor-bearing mice in vivo and effectively alleviated splenomegaly caused by the malignant tumor. Immunohistochemical staining analysis of E-cadherin, Vimentin, and β-catenin confirmed that the inversion of the EMT was also achieved in solid tumors. These results highlight the potential of SL and DOX combined chemotherapeutic strategy for eliminating breast carcinoma. STATEMENT OF SIGNIFICANCE: Cancer stem cells (CSCs), as an important part of tumor heterogeneity, can survive against conventional chemotherapy and initiate tumorigenesis, recurrence, and metastasis. Moreover, non-CSCs can convert into the CSC state through the abnormal Wnt/β-catenin pathway, which is closely related to the epithelial-mesenchymal transition (EMT) process. Here, redox-degradable binary drug-loaded micelles (PPH/DOX+SL) were designed to target CSCs and overcome drug resistance of breast cancer cells. The combined chemotherapy of salinomycin (SL) and doxorubicin (DOX) reversed drug resistance, while the PPH/DOX+SL micelles enhanced the intracellular accumulation and drug penetration of BCSC spheres. The introduction of SL downregulated the expression of tumor stemness genes and the Wnt/β-catenin pathway-related genes and inverted the EMT process. PPH/DOX+SL continuously inhibited tumor growth and invasion in vivo.

Evolution of intra-tumoral heterogeneity across different pathological stages in papillary thyroid carcinoma

BACKGROUND

Intra-tumor heterogeneity (ITH) results from the continuous accumulation of mutations during disease progression, thus impacting patients' clinical outcome. How the ITH evolves across papillary thyroid carcinoma (PTC) different tumor stages is lacking.

METHODS

We used the whole-exome sequencing data from The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) cohort to track the ITH and assessed its relationship with clinical features through different stages of the PTC progression. We further assayed the expression levels of the specific genes in papillary thyroid cancer cell lines compared to an immortalized normal thyroid epithelial cell line by qRT-PCR.

RESULTS

We revealed the timing of mutational processes and the dynamics of the temporal acquisition of somatic events during the lifetime of the PTC. ITH significantly influences the PTC patient's survival rate and, as genetic heterogeneity increases, the prognosis gets worse in advanced tumor stages. ITH also affects the mutational architecture of each clinical stage which is subject to periodic fluctuations. Different mutational processes may cooperate to shape a stage-specific mutational spectrum during the progression from early to advanced tumor stages. Moreover, different evolutionary paths characterize PTC progression across pathological stages due to both mutations recurrently occurring in all stages in hotspot positions and distinct codon changes dominating in different stages. A different expression level of specific genes also exists in different thyroid cancer cell lines.

CONCLUSIONS

Our findings suggest ITH as a potential unfavorable prognostic factor in PTC and highlight the dynamic changes in different clinical stages of PTC, providing some clues for the precision medicine and suggesting different diagnostic decisions depending on the clinical stages of patients. Finally, complete clear guidelines to define risk stratification of PTC patients are lacking; thus, this work could contribute to defining patients who need more aggressive treatments and, in turn, could reduce the social burden of this cancer.

Clonal evolution in primary breast cancers under sequential epirubicin and docetaxel monotherapy

Background

Subclonal evolution during primary breast cancer treatment is largely unexplored. We aimed to assess the dynamic changes in subclonal composition of treatment-naïve breast cancers during neoadjuvant chemotherapy.

Methods

We performed whole exome sequencing of tumor biopsies collected before, at therapy switch, and after treatment with sequential epirubicin and docetaxel monotherapy in 51 out of 109 patients with primary breast cancer, who were included in a prospectively registered, neoadjuvant single-arm phase II trial.

Results

There was a profound and differential redistribution of subclones during epirubicin and docetaxel treatment, regardless of therapy response. While truncal mutations and main subclones persisted, smaller subclones frequently appeared or disappeared. Reassessment of raw data, beyond formal mutation calling, indicated that the majority of subclones seemingly appearing during treatment were in fact present in pretreatment breast cancers, below conventional detection limits. Likewise, subclones which seemingly disappeared were still present, below detection limits, in most cases where tumor tissue remained. Tumor mutational burden (TMB) dropped during neoadjuvant therapy, and copy number analysis demonstrated specific genomic regions to be systematically lost or gained for each of the two chemotherapeutics.

Conclusions

Sequential epirubicin and docetaxel monotherapy caused profound redistribution of smaller subclones in primary breast cancer, while early truncal mutations and major subclones generally persisted through treatment.

Trial registration

ClinicalTrials.gov, NCT00496795, registered on July 4, 2007.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01090-2.

MOSCATO: a supervised approach for analyzing multi-Omic single-Cell data

Background

Advancements in genomic sequencing continually improve personalized medicine, and recent breakthroughs generate multimodal data on a cellular level. We introduce MOSCATO, a technique for selecting features across multimodal single-cell datasets that relate to clinical outcomes. We summarize the single-cell data using tensors and perform regularized tensor regression to return clinically-associated variable sets for each ‘omic’ type.

Results

Robustness was assessed over simulations based on available single-cell simulation methods, and applicability was assessed through an example using CITE-seq data to detect genes associated with leukemia. We find that MOSCATO performs favorably in selecting network features while also shown to be applicable to real multimodal single-cell data.

Conclusions

MOSCATO is a useful analytical technique for supervised feature selection in multimodal single-cell data. The flexibility of our approach enables future extensions on distributional assumptions and covariate adjustments.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08759-3).

Optical Cellular Micromotion: A New Paradigm to Measure Tumor Cells Invasion within Gels Mimicking the 3D Tumor Environments

Measuring tumor cell invasiveness through 3D tissues, particularly at the single-cell level, can provide important mechanistic understanding and assist in identifying therapeutic targets of tumor invasion. However, current experimental approaches, including standard in vitro invasion assays, have limited physiological relevance and offer insufficient insight into the vast heterogeneity in tumor cell migration through tissues. To address these issues, here the concept of optical cellular micromotion is reported on, where digital holographic microscopy is used to map the optical nano- to submicrometer thickness fluctuations within single-cells. These fluctuations are driven by the dynamic movement of subcellular structures including the cytoskeleton and inherently associated with the biological processes involved in cell invasion within tissues. It is experimentally demonstrated that the optical cellular micromotion correlates with tumor cells motility and invasiveness both at the population and single-cell levels. In addition, the optical cellular micromotion significantly reduced upon treatment with migrastatic drugs that inhibit tumor cell invasion. These results demonstrate that micromotion measurements can rapidly and non-invasively determine the invasive behavior of single tumor cells within tissues, yielding a new and powerful tool to assess the efficacy of approaches targeting tumor cell invasiveness.

New Advances in Nano-Drug Delivery Systems: Helicobacter pylori and Gastric Cancer

With the development of materials science and biomedicine, the application of nanomaterials in the medical field is further promoted. In the process of the diagnosis and treatment of diseases, a variety of drugs need to be used. It is an ideal state to make these drugs arrive at a specific location at a specific time and release at a specific speed, which can improve the bioavailability of drugs and reduce the adverse effects of drugs on normal tissues. Traditional drug delivery methods such as tablets, capsules, syrups, and ointments have certain limitations. The emergence of a new nano-drug delivery system further improves the accuracy of drug delivery and the efficacy of drugs. It is well known that the development of the cancer of the stomach is the most serious consequence for the infection of Helicobacter pylori. For the patients who are suffering from gastric cancer, the treatments are mainly surgery, chemotherapy, targeted and immune therapy, and other comprehensive treatments. Although great progress has been made, the diagnosis and prognosis of gastric cancer are still poor with patients usually diagnosed with cancer at an advanced stage. Current treatments are of limited benefits for patients, resulting in a poor 5-year survival rate. Nanomaterials may play a critical role in early diagnosis. A nano-drug delivery system can significantly improve the chemotherapy, targeted therapy, and immunotherapy of advanced gastric cancer, reduce the side effects of the original treatment plan and provide patients with better benefits. It is a promising treatment for gastric cancer. This article introduces the application of nanomaterials in the diagnosis and treatment of H. pylori and gastric cancer.

Acquired chemoresistance drives spatial heterogeneity, chemoprotection and collective migration in pancreatic tumor spheroids

Tumors display rich cellular heterogeneity and typically consist of multiple co-existing clones with distinct genotypic and phenotypic characteristics. The acquisition of resistance to chemotherapy has been shown to contribute to the development of aggressive cancer traits, such as increased migration, invasion and stemness. It has been hypothesized that collective cellular behavior and cooperation of cancer cell populations may directly contribute to disease progression and lack of response to treatment. Here we show that the spontaneous emergence of chemoresistance in a cancer cell population exposed to the selective pressure of a chemotherapeutic agent can result in the emergence of collective cell behavior, including cell-sorting, chemoprotection and collective migration. We derived several gemcitabine resistant subclones from the human pancreatic cancer cell line BxPC3 and determined that the observed chemoresistance was driven of a focal amplification of the chr11p15.4 genomic region, resulting in over-expression of the ribonucleotide reductase (RNR) subunit RRM1. Interestingly, these subclones display a rich cell-sorting behavior when cultured as mixed tumor spheroids. Furthermore, we show that chemoresistant cells are able to exert a chemoprotective effect on non-resistant cells in spheroid co-culture, whereas no protective effect is seen in conventional 2D culture. We also demonstrate that the co-culture of resistant and non-resistant cells leads to collective migration where resistant cells enable migration of otherwise non-migratory cells.

Molecular Hydrogen Inhibits Colorectal Cancer Growth via the AKT/SCD1 Signaling Pathway

Objective

Molecular hydrogen (H₂) has been considered a potential therapeutic target in many cancers. Therefore, we sought to assess the potential effect of H₂ on colorectal cancer (CRC) in this study.

Methods

The effect of H₂ on the proliferation and apoptosis of RKO, SW480, and HCT116 CRC cell lines was assayed by CCK-8, colony formation, and flow cytometry assays. The effect of H₂ on tumor growth was observed in xenograft implantation models (inhalation of 67% hydrogen two hours per day). Western blot and immunohistochemistry analyses were performed to examine the expression of p-PI3K, PI3K, AKT, pAKT, and SCD1 in CRC cell lines and xenograft mouse models. The expression of SCD1 in 491 formalin-fixed, paraffin-embedded CRC specimens was investigated with immunochemistry. The relationship between SCD1 status and clinicopathological characteristics and outcomes was determined.

Results

Hydrogen treatment suppressed the proliferation of CRC cell lines independent of apoptosis, and the cell lines showed different responses to different doses of H₂. Hydrogen also elicited a potent antitumor effect to reduce CRC tumor volume and weight in vivo. Western blot and IHC staining demonstrated that H₂ inhibits CRC cell proliferation by decreasing pAKT/SCD1 levels, and the inhibition of cell proliferation induced by H₂ was reversed by the AKT activator SC79. IHC showed that SCD1 expression was significantly higher in CRC tissues than in normal epithelial tissues (70.3% vs. 29.7%, p = 0.02) and was correlated with a more advanced TNM stage (III vs. I + II; 75.9% vs. 66.3%, p = 0.02), lymph node metastasis (with vs. without; 75.9% vs. 66.3%, p = 0.02), and patients without a family history of CRC (78.7% vs. 62.1%, p = 0.047).

Conclusion

This study demonstrates that high concentrations of H₂ exert an inhibitory effect on CRC by inhibiting the pAKT/SCD1 pathway. Further studies are warranted for clinical evaluation of H₂ as SCD1 inhibitor to target CRC.

DrugCVar: a platform for evidence-based drug annotation for genetic variants in cancer

Motivation

Targeted therapy for cancer-related genetic variants is critical for precision medicine. Although several databases including The Clinical Interpretation of Variants in Cancer (CIViC), The Oncology Knowledge Base (OncoKB), The Cancer Genome Interpreter (CGI), My Cancer Genome (MCG) provide clinical interpretations of variants in cancer, the clinical evidence was limited and miscellaneous. In this study, we developed the DrugCVar database, which integrated our manually curated cancer variant-drug targeting evidence from literature and the interpretations from the public resources.

Results

In total, 7,830 clinical evidences for cancer variant-drug targeting were integrated and classified into ten evidence tiers. Searching and browsing functions were provided for quick queries of cancer variant-drug targeting evidence. Also, batch annotation module was developed for user-provided massive genetic variants in various formats. Details such as the mutation function, location of the variants in gene and protein structures, and mutation statistics of queried genes in various tumor types were also provided for further investigations. Thus, DrugCVar could serve as a comprehensive annotation tool to interpret potential drugs for cancer variants especially the massive ones from clinical cancer genomics studies.

Availability and implementation

The database is available at http://drugcvar.omicsbio.info.

Supplementary information

Supplementary data are available at Bioinformatics online.

Bioresponsive Nanomaterials: Recent Advances in Cancer Multimodal Imaging and Imaging-Guided Therapy

Cancer is a serious health problem which increasingly causes morbidity and mortality worldwide. It causes abnormal and uncontrolled cell division. Traditional cancer treatments include surgery, chemotherapy, radiotherapy and so on. These traditional therapies suffer from high toxicity and arouse safety concern in normal area and have difficulty in accurately targeting tumour. Recently, a variety of nanomaterials could be used for cancer diagnosis and therapy. Nanomaterials have several advantages, e.g., high concentration in tumour via targeting design, reduced toxicity in normal area and controlled drug release after various rational designs. They can combine with many types of biomaterials in order to improve biocompatibility. In this review, we outlined the latest research on the use of bioresponsive nanomaterials for various cancer imaging modalities (magnetic resonance imaging, positron emission tomography and phototacoustic imaging) and imaging-guided therapy means (chemotherapy, radiotherapy, photothermal therapy and photodynamic therapy), followed by discussing the challenges and future perspectives of this bioresponsive nanomaterials in biomedicine.

Clinical utility of PDX cohorts to reveal biomarkers of intrinsic resistance and clonal architecture changes underlying acquired resistance to cetuximab in HNSCC

Cetuximab is a widely used drug for treating head and neck squamous cell carcinomas (HNSCCs); however, it provides restricted clinical benefits, and its response duration is limited by drug resistance. Here, we conducted randomized “Phase II-like clinical trials” of 49 HNSCC PDX models and reveal multiple informative biomarkers for intrinsic resistance to cetuximab (e.g., amplification of ANKH, up-regulation of PARP3). After validating these intrinsic resistance biomarkers in another HNSCC PDX cohort (61 PDX models), we generated acquired cetuximab resistance PDX models and analyzed them to uncover resistance mechanisms. Whole exome sequencing and transcriptome sequencing revealed diverse patterns of clonal selection in acquired resistant PDXs, including the emergence of subclones with strongly activated RAS/MAPK. Extending these insights, we show that a combination of a RAC1/RAC3 dual-target inhibitor and cetuximab could overcome acquired cetuximab resistance in vitro and in vivo. Beyond revealing intrinsic resistance biomarkers, our PDX-based study shows how clonal architecture changes underlying acquired resistance can be targeted to expand the therapeutic utility of this important drug to more HNSCC patients.

Longitudinal single-cell RNA-seq analysis reveals stress-promoted chemoresistance in metastatic ovarian cancer

Chemotherapy resistance is a critical contributor to cancer mortality and thus an urgent unmet challenge in oncology. To characterize chemotherapy resistance processes in high-grade serous ovarian cancer, we prospectively collected tissue samples before and after chemotherapy and analyzed their transcriptomic profiles at a single-cell resolution. After removing patient-specific signals by a novel analysis approach, PRIMUS, we found a consistent increase in stress-associated cell state during chemotherapy, which was validated by RNA in situ hybridization and bulk RNA sequencing. The stress-associated state exists before chemotherapy, is subclonally enriched during the treatment, and associates with poor progression-free survival. Co-occurrence with an inflammatory cancer-associated fibroblast subtype in tumors implies that chemotherapy is associated with stress response in both cancer cells and stroma, driving a paracrine feed-forward loop. In summary, we have found a resistant state that integrates stromal signaling and subclonal evolution and offers targets to overcome chemotherapy resistance.

Current Trends in Precision Medicine and Next-Generation Sequencing in Head and Neck Cancer

OPINION STATEMENT

As the field of oncology enters the era of precision medicine and targeted therapies, we have come to realize that there may be no single "magic bullet" for patients with head and neck cancer. While immune check point inhibitors and some targeted therapeutics have shown great promise in improving oncologic outcomes, the current standard of care in most patients with head and neck squamous cell carcinoma (HNSCC) remains a combination of surgery, radiation, and/or cytotoxic chemotherapy. Nevertheless, advances in precision medicine, next-generation sequencing (NGS), and targeted therapies have a potential future in the treatment of HNSCC. These roles include increased patient treatment stratification based on predictive biomarkers or targetable mutations and novel combinatorial regimens with existing HNSCC treatments. There remain challenges to precision medicine and NGS in HNSCC, including intertumor and intratumor heterogeneity, challenging targets, and need for further trials validating the utility of NGS and precision medicine. Additionally, there is a need for evidence-based practice guidelines to assist clinicians on how to appropriately incorporate NGS in care for HNSCC. In this review, we describe the current state of precision medicine and NGS in HNSCC and opportunities for future advances in this challenging but important field.

Magnetic Resonance Imaging Phenotypes of Breast Cancer Molecular Subtypes: A Systematic Review

OBJECTIVE

Magnetic resonance imaging (MRI) is the most sensitive imaging modality in detecting breast cancer. The purpose of this systematic review is to investigate the role of human extracted MRI phenotypes in classifying molecular subtypes of breast cancer.

METHODS

We performed a literature search of published articles on the application of MRI phenotypic features in invasive breast cancer molecular subtype classifications by radiologists' interpretation on Medline Complete, Pubmed, and Google scholar from 1st January 2000 to 31st March 2021. Of the 1453 literature identified, 42 fulfilled the inclusion criteria.

RESULTS

All studies were case-controlled, retrospective study and research-based. The majority of the studies assessed the MRI features using American College of Radiology- Breast Imaging Reporting and Data System (ACR-BIRADS) classification and using dynamic contrast-enhanced (DCE) kinetic features, Apparent Diffusion Coefficient (ADC) values, and T2 sequence. Most studies divided invasive breast cancer into 4 main subtypes, luminal A, luminal B, HER2, and triple-negative (TN) cancers, and used 2 readers. We present a summary of the radiologists' extracted breast MRI phenotypical features and their correlating breast cancer subtypes classifications. The characteristic features are morphology, enhancement kinetics, and T2 signal intensity. We found that the TN subtype has the most distinctive MRI features compared to the other subtypes and luminal A and B have many similar features.

CONCLUSION

The MRI features which are predictive of each subtype are the morphology, internal enhancement features, and T2 signal intensity, predominantly between TN and the rest. Radiologists' visual interpretation of some of MRI features may offer insight into the respective invasive breast cancer molecular subtype. However, current evidence are still limited to "suggestive" features instead of a diagnostic standard.  Further research is recommended to explore this potential application, for example, by augmentation of radiologists' visual interpretation by artificial intelligence.

A Prospective Observational Study of Osimertinib for Chemo-Naive Elderly Patients with EGFR Mutation-Positive Non-Small Cell Lung Cancer

Background

The clinical outcomes of elderly patients with EGFR-mutated non-small cell lung cancer (NSCLC) who are treated with osimertinib have not been sufficiently evaluated. This study aimed to assess the efficacy and safety of osimertinib in elderly chemotherapy-naive patients with NSCLC harboring sensitive EGFR mutations.

Patients and Methods

We assessed the clinical effects of osimertinib as a first-line treatment for elderly NSCLC patients (≥75 years of age) with an exon 19 deletion or exon 21 L858R mutation in EGFR. All patients were administered 80 mg/day osimertinib as initial treatment.

Results

Forty-three patients (24 women and 19 men) with adenocarcinoma who were treated between August 2018 and July 2021 were included in this study; their median age was 79 years (range, 75-90 years). The overall objective response rate was 60.5%. The median progression-free survival (PFS) and time to treatment failure (TTF) of the entire patient population were 22.1 months and 14.6 months, respectively. The most common adverse event was rash acneiform (42%), followed by diarrhea (33%) and paronychia (28%); none of these were grades ≥3. Interstitial lung disease developed in 8 patients (18.6%); however, no treatment-related deaths occurred. Multivariate analysis identified performance status and disease stage as predictors of PFS and TTF.

Conclusion

Considering the findings of this study and despite an observed discordance between PFS and TTF, osimertinib appears to be an effective and safe treatment option in elderly patients with advanced NSCLC harboring sensitive EGFR mutations. To obtain conclusive results, further studies in a larger elderly population are warranted.

Post-Progression Survival Highly Influences Overall Survival in Driver Gene Mutation/Translocation Negative or Unknown Type of Non-Small Cell Lung Cancer

INTRODUCTION

In stage I-III non-small cell lung cancer (NSCLC), which is considered operable, surgical resection is the most efficacious treatment and is considered to provide a cure. However, after complete surgical resection, approximately 50% of patients with stage I-IIIA NSCLC experience recurrence and death. Once postoperative recurrence of NSCLC occurs, the prognosis is significantly poor, and the course of treatment after recurrence may influence overall survival (OS). Consequently, we investigated the relationship between relapse-free survival (RFS), post-progression survival (PPS), and OS in patients with postoperative recurrence of NSCLC with driver gene mutation/translocation negative or unknown status.

METHODS

Between January 2007 and September 2019, 101 patients with driver gene mutation/translocation negative or unknown status of NSCLC who underwent complete resection and in whom recurrence occurred were analyzed. The associations between RFS, PPS, and OS were analyzed at the individual patient level.

RESULTS

Linear regression and Spearman rank correlation analyses revealed that PPS was strongly associated with OS (r = 0.83, p < 0.0001, R2 = 0.71), whereas RFS was moderately correlated with OS (r = 0.65, p < 0.0001, R2 = 0.48). In the multivariate analysis, performance status at relapse, administration of immune checkpoint inhibitors, and radiotherapy for oligo-recurrences were significantly associated with PPS (p < 0.001).

CONCLUSION

Current analysis of individual-level data of patients who underwent complete resection implied that PPS had a higher impact on OS than RFS in patients with postoperative recurrence of driver gene mutation/translocation negative or unknown status of NSCLC. Additionally, current perceptions indicate that treatment beyond progression after complete surgical resection might strongly affect OS.

A Portrait of Intratumoral Genomic and Transcriptomic Heterogeneity at Single-Cell Level in Colorectal Cancer

In the study of cancer, omics technologies are supporting the transition from traditional clinical approaches to precision medicine. Intra-tumoral heterogeneity (ITH) is detectable within a single tumor in which cancer cell subpopulations with different genome features coexist in a patient in different tumor areas or may evolve/differ over time. Colorectal carcinoma (CRC) is characterized by heterogeneous features involving genomic, epigenomic, and transcriptomic alterations. The study of ITH is a promising new frontier to lay the foundation towards successful CRC diagnosis and treatment. Genome and transcriptome sequencing together with editing technologies are revolutionizing biomedical research, representing the most promising tools for overcoming unmet clinical and research challenges. Rapid advances in both bulk and single-cell next-generation sequencing (NGS) are identifying primary and metastatic intratumoral genomic and transcriptional heterogeneity. They provide critical insight in the origin and spatiotemporal evolution of genomic clones responsible for early and late therapeutic resistance and relapse. Single-cell technologies can be used to define subpopulations within a known cell type by searching for differential gene expression within the cell population of interest and/or effectively isolating signal from rare cell populations that would not be detectable by other methods. Each single-cell sequencing analysis is driven by clustering of cells based on their differentially expressed genes. Genes that drive clustering can be used as unique markers for a specific cell population. In this review we analyzed, starting from published data, the possible achievement of a transition from clinical CRC research to precision medicine with an emphasis on new single-cell based techniques; at the same time, we focused on all approaches and issues related to this promising technology. This transition might enable noninvasive screening for early diagnosis, individualized prediction of therapeutic response, and discovery of additional novel drug targets.

Homocystamide Conjugates of Human Serum Albumin as a Platform to Prepare Bimodal Multidrug Delivery Systems for Boron Neutron Capture Therapy

Boron neutron capture therapy is a unique form of adjuvant cancer therapy for various malignancies including malignant gliomas. The conjugation of boron compounds and human serum albumin (HSA)-a carrier protein with a long plasma half-life-is expected to extend systemic circulation of the boron compounds and increase their accumulation in human glioma cells. We report on the synthesis of fluorophore-labeled homocystamide conjugates of human serum albumin and their use in thiol-'click' chemistry to prepare novel multimodal boronated albumin-based theranostic agents, which could be accumulated in tumor cells. The novelty of this work involves the development of the synthesis methodology of albumin conjugates for the imaging-guided boron neutron capture therapy combination. Herein, we suggest using thenoyltrifluoroacetone as a part of an anticancer theranostic construct: approximately 5.4 molecules of thenoyltrifluoroacetone were bound to each albumin. Along with its beneficial properties as a chemotherapeutic agent, thenoyltrifluoroacetone is a promising magnetic resonance imaging agent. The conjugation of bimodal HSA with undecahydro-closo-dodecaborate only slightly reduced human glioma cell line viability in the absence of irradiation (~30 μM of boronated albumin) but allowed for neutron capture and decreased tumor cell survival under epithermal neutron flux. The simultaneous presence of undecahydro-closo-dodecaborate and labeled amino acid residues (fluorophore dye and fluorine atoms) in the obtained HSA conjugate makes it a promising candidate for the combination imaging-guided boron neutron capture therapy.

ΔCT Value of Amplified Refractory Mutation System Predicts Efficacy of EGFR-TKIs in Advanced Non-Small-Cell Lung Cancer: A Multi-Center Retrospective Study

Purpose: This multi-center retrospective study determines whether the ΔCT value of the Amplified Refractory Mutation System (ARMS) predicts the efficacy of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) in EGFR-mutant advanced non-small-cell lung cancer (NSCLC). Patients and methods: Patients who harbored an exon 19 deletion (19Del) or L858R mutation detected by the ARMS and previously received treatment of EGFR-TKIs as a monotherapy were enrolled. A total of 108 NSCLC patients in four hospitals were enrolled. We divided the patients into a high ΔCT group (Group H) and a low ΔCT group (Group L) by the Martingale residuals analysis and log-rank test. The primary outcome was progression-free survival (PFS). Univariate analysis and multivariable regression were applied to compare the PFS between the groups. Result: The Martingale residuals analysis and log-rank test were applied to find the cutoff ΔCT value (0.8). In the 108 patients we enrolled, 59 were in group L and 49 were in group H. Patients' demographics and clinical characteristics, including age, sex, smoking history, pathology, mutation sites, TNM stage, and line of TKIs therapy, were not significantly different between group L and group H. The median PFS was 11.1 months in group L and 6.9 months in group H, and the difference showed statistical significance (p < 0.001). Moreover, the objective response rates (ORRs) in group L was significantly higher than in group H (61.0 vs 34.7%, p = 0.002). The median OS was 25.0 months in group L and 20.0 months in group H (p = 0.046). Conclusion: The ΔCT value of ARMS could be an efficacy predictor for EGFR-TKI treatment in advanced EGFR-mutant NSCLC.

Response prediction of neoadjuvant chemoradiation therapy in locally advanced rectal cancer using CT-based fractal dimension analysis

OBJECTIVES

There are individual variations in neo-adjuvant chemoradiation therapy (nCRT) in patients with locally advanced rectal cancer (LARC). No reliable modality currently exists that can predict the efficacy of nCRT. The purpose of this study is to assess if CT-based fractal dimension and filtration-histogram texture analysis can predict therapeutic response to nCRT in patients with LARC.

METHODS

In this retrospective study, 215 patients (average age: 57 years (18-87 years)) who received nCRT for LARC between June 2005 and December 2016 and underwent a staging diagnostic portal venous phase CT were identified. The patients were randomly divided into two datasets: a training set (n = 170), and a validation set (n = 45). Tumor heterogeneity was assessed on the CT images using fractal dimension (FD) and filtration-histogram texture analysis. In the training set, the patients with pCR and non-pCR were compared in univariate analysis. Logistic regression analysis was applied to identify the predictive value of efficacy of nCRT and receiver operating characteristic analysis determined optimal cutoff value. Subsequently, the most significant parameter was assessed in the validation set.

RESULTS

Out of the 215 patients evaluated, pCR was reached in 20.9% (n = 45/215) patients. In the training set, 7 out of 37 texture parameters showed significant difference comparing between the pCR and non-pCR groups and logistic multivariable regression analysis incorporating clinical and 7 texture parameters showed that only FD was associated with pCR (p = 0.001). The area under the curve of FD was 0.76. In the validation set, we applied FD for predicting pCR and sensitivity, specificity, and accuracy were 60%, 89%, and 82%, respectively.

CONCLUSION

FD on pretreatment CT is a promising parameter for predicting pCR to nCRT in patients with LARC and could be used to help make treatment decisions.

KEY POINTS

• Fractal dimension analysis on pretreatment CT was associated with response to neo-adjuvant chemoradiation in patients with locally advanced rectal cancer. • Fractal dimension is a promising biomarker for predicting pCR to nCRT and may potentially select patients for individualized therapy.

CK1δ stimulates ubiquitination-dependent proteasomal degradation of ATF4 to promote chemoresistance in gastric Cancer

Chemoresistance remains a major obstacle to successful cancer therapy, especially for advanced cancers. It used to be recognised as a stable outcome resulting from genetic changes. However, recent studies showed that chemoresistance can also be unstable and reversible with the involvement of non-genetic alterations. In the present study, we found that activating transcription factor 4 (ATF4) is downregulated in chemoresistant gastric cancer cells. The over-expression of ATF4 reversed chemoresistance by activating CHOP transcription to enhance drug-induced apoptosis, and vice versa. Moreover, casein kinase 1 delta (CK1δ) was identified as the kinase responsible for ATF4-S219 phosphorylation, which triggered βTrCP-mediated ATF4 polyubiquitination to promote its proteasomal degradation subsequently. Interestingly, drug withdrawal gradually restored chemosensitivity as well as ATF4 expression in chemoresistant cells, highlighting the dependence of dynamic drug resistance on ATF4 protein expression. In line with these findings, the inhibition of ATF4 protein degradation by CK1δ or proteasome inhibitors overcame chemoresistance both in vitro and in vivo. Taken together, these results indicate that CK1δ stimulates βTrCP-dependent ATF4 polyubiquitination and subsequent proteasomal degradation to promote chemoresistance in gastric cancer. Stabilisation of the ATF4 protein with bortezomib (BTZ), an anticancer drug that inhibits proteasomal degradation, might be a rational strategy to improve chemotherapeutic efficacy in gastric cancer.