A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models.

Idiopathic pulmonary fibrosis (IPF) is an aggressive interstitial lung disease with a high mortality rate. Putative drug targets in IPF have failed to translate into effective therapies at the clinical level. We identify TRAF2- and NCK-interacting kinase (TNIK) as an anti-fibrotic target using a predictive artificial intelligence (AI) approach. Using AI-driven methodology, we generated INS018_055, a small-molecule TNIK inhibitor, which exhibits desirable drug-like properties and anti-fibrotic activity across different organs in vivo through oral, inhaled or topical administration. INS018_055 possesses anti-inflammatory effects in addition to its anti-fibrotic profile, validated in multiple in vivo studies. Its safety and tolerability as well as pharmacokinetics were validated in a randomized, double-blinded, placebo-controlled phase I clinical trial (NCT05154240) involving 78 healthy participants. A separate phase I trial in China, CTR20221542, also demonstrated comparable safety and pharmacokinetic profiles. This work was completed in roughly 18 months from target discovery to preclinical candidate nomination and demonstrates the capabilities of our generative AI-driven drug-discovery pipeline.

Evolutionary dynamics of tipifarnib in HRAS mutated head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) is a highly prevalent malignancy worldwide, with a significant proportion of patients developing recurrent and/or metastatic (R/M) disease. Despite recent advances in therapy, the prognosis for patients with advanced HNSCC remains poor. Here, we present the case of a patient with recurrent metastatic HNSCC harboring an HRAS G12S mutation who achieved a durable response to treatment with tipifarnib, a selective inhibitor of farnesyltransferase. The patient was a 48-year-old woman who had previously received multiple lines of therapy with no significant clinical response. However, treatment with tipifarnib resulted in a durable partial response that lasted 8 months. Serial genomic and transcriptomic analyses demonstrated upregulation of YAP1 and AXL in metastatic lesions compared with the primary tumor, the evolution of the tumor microenvironment from an immune-enriched to a fibrotic subtype with increased angiogenesis, and activation of the PI3K/AKT/mTOR pathway in tipifarnib treatment. Lastly, in HRAS-mutated PDXs and in the syngeneic HRAS model, we demonstrated that tipifarnib efficacy is limited by activation of the AKT pathway, and dual treatment with tipifarnib and the PI3K inhibitor, BYL719, resulted in enhanced anti-tumor efficacy. Our case study highlights the potential of targeting HRAS mutations with tipifarnib in R/M HNSCC and identifies potential mechanisms of acquired resistance to tipifarnib, along with immuno-, chemo-, and radiation therapy. Preclinical results provide a firm foundation for further investigation of drug combinations of HRAS-and PI3K -targeting therapeutics in R/M HRAS-driven HNSCC.

A comprehensive AI-driven analysis of large-scale omic datasets reveals novel dual-purpose targets for the treatment of cancer and aging.

As aging and tumorigenesis are tightly interconnected biological processes, targeting their common underlying driving pathways may induce dual-purpose anti-aging and anti-cancer effects. Our transcriptomic analyses of 16,740 healthy samples demonstrated tissue-specific age-associated gene expression, with most tumor suppressor genes downregulated during aging. Furthermore, a large-scale pan-cancer analysis of 11 solid tumor types (11,303 cases and 4431 control samples) revealed that many cellular processes, such as protein localization, DNA replication, DNA repair, cell cycle, and RNA metabolism, were upregulated in cancer but downregulated in healthy aging tissues, whereas pathways regulating cellular senescence were upregulated in both aging and cancer. Common cancer targets were identified by the AI-driven target discovery platform-PandaOmics. Age-associated cancer targets were selected and further classified into four groups based on their reported roles in lifespan. Among the 51 identified age-associated cancer targets with anti-aging experimental evidence, 22 were proposed as dual-purpose targets for anti-aging and anti-cancer treatment with the same therapeutic direction. Among age-associated cancer targets without known lifespan-regulating activity, 23 genes were selected based on predicted dual-purpose properties. Knockdown of histone demethylase KDM1A, one of these unexplored candidates, significantly extended lifespan in Caenorhabditis elegans. Given KDM1A's anti-cancer activities reported in both preclinical and clinical studies, our findings propose KDM1A as a promising dual-purpose target. This is the first study utilizing an innovative AI-driven approach to identify dual-purpose target candidates for anti-aging and anti-cancer treatment, supporting the value of AI-assisted target identification for drug discovery.

Microbial Changes Associated With Oral Cavity Cancer Progression.

OBJECTIVE: To examine the oral microbiome in the context of oral cavity squamous cell carcinoma. STUDY DESIGN: Basic science research. SETTING: Academic medical center. METHODS: Oral swabs were collected from patients presenting to the operating room for management of oral cavity squamous cell carcinoma and from age- and sex-matched control patients receiving surgery for unrelated benign conditions. 16S ribosomal RNA (rRNA) sequencing was performed on genetic material obtained from swabs. A bacterial rRNA gene library was created and sequence reads were sorted into taxonomic units. RESULTS: Thirty-one control patients (17 males) and 35 cancer patients (21 males) were enrolled. Ages ranged from 23 to 89 (median 63) for control patients and 35 to 86 (median 66) for cancer patients. Sixty-one percent of control patients and 63% of cancer patients were smokers. 16S analyses demonstrated a significant decrease in Streptococcus genera in oral cancer patients (34.11% vs 21.74% of the population, p = .04). Increases in Fusobacterium, Peptostreptococcus, Parvimonas, and Neisseria were also found. The abundance of these bacteria correlated with tumor T-stage. CONCLUSION: 16S rRNA sequencing demonstrated changes in bacterial populations in oral cavity cancer and its progression compared to noncancer controls. We found increases in bacteria genera that correspond with tumor stage-Fusobacteria, Peptostreptococcus, Parvimonas, Neisseria, and Treponema. These data suggest that oral cancer creates an environment to facilitate foreign bacterial growth, rather than implicating a specific bacterial species in carcinogenesis. These bacteria can be employed as a potential marker for tumor progression or interrogated to better characterize the tumor microenvironment.

Epstein-Barr Virus DNA Screening in Asymptomatic People without Known Nasopharyngeal Cancer.

Nasopharyngeal carcinoma is an uncommon head and neck malignancy in most parts of the world but is endemic in Southeast Asia and North Africa.1 Over 130,000 new cases were recorded globally and 80,000 patients succumbed to nasopharyngeal carcinoma in 2020.2 Owing to relatively mild symptoms during early stages, most patients are diagnosed with clinically advanced disease, and the 5-year overall survival for these patients remains approximately 50%.3 Hence, early detection when the disease is most treatable may improve clinical outcomes.

High-confidence cancer patient stratification through multiomics investigation of DNA repair disorders.

Multiple cancer types have limited targeted therapeutic options, in part due to incomplete understanding of the molecular processes underlying tumorigenesis and significant intra- and inter-tumor heterogeneity. Identification of novel molecular biomarkers stratifying cancer patients with different survival outcomes may provide new opportunities for target discovery and subsequent development of tailored therapies. Here, we applied the artificial intelligence-driven PandaOmics platform ( https://pandaomics.com/ ) to explore gene expression changes in rare DNA repair-deficient disorders and identify novel cancer targets. Our analysis revealed that CEP135, a scaffolding protein associated with early centriole biogenesis, is commonly downregulated in DNA repair diseases with high cancer predisposition. Further screening of survival data in 33 cancers available at TCGA database identified sarcoma as a cancer type where lower survival was significantly associated with high CEP135 expression. Stratification of cancer patients based on CEP135 expression enabled us to examine therapeutic targets that could be used for the improvement of existing therapies against sarcoma. The latter was based on application of the PandaOmics target-ID algorithm coupled with in vitro studies that revealed polo-like kinase 1 (PLK1) as a potential therapeutic candidate in sarcoma patients with high CEP135 levels and poor survival. While further target validation is required, this study demonstrated the potential of in silico-based studies for a rapid biomarker discovery and target characterization.

OrganoID: A versatile deep learning platform for tracking and analysis of single-organoid dynamics.

Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses. However, these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (95%) and size (97%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified strong dose effect sizes on organoid circularity, solidity, and eccentricity. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications.

Phase I study of nab-paclitaxel-based induction followed by nab-paclitaxel-based concurrent chemotherapy and re-irradiation in previously treated head and neck squamous cell carcinoma.

BACKGROUND: Recurrent head and neck squamous cell carcinoma (HNSCC) is associated with poor overall survival (OS). Prior studies suggested incorporation of nab-paclitaxel (A) may improve outcomes in recurrent HNSCC. METHODS: This Phase I study evaluated induction with carboplatin and A followed by concomitant FHX (infusional 5-fluorouracil, hydroxyurea and twice-daily radiation therapy administered every other week) plus A with cohort dose escalation ranging from 10-100 mg/m2 in recurrent HNSCC. The primary endpoint was maximally tolerated dose (MTD) and dose-limiting toxicity (DLT) of A when given in combination with FHX (AFHX). RESULTS: Forty-eight eligible pts started induction; 28 pts started AFHX and were evaluable for toxicity. Two DLTs occurred (both Grade 4 mucositis) at a dose level 20 mg/m2. No further DLTs were observed with subsequent dose escalation. The MTD and recommended Phase II dose (RP2D) of A was 100 mg/m2. CONCLUSIONS: In this Phase I study, the RP2D of A with FHX is 100 mg/m2 (AFHX). The role of re-irradiation with immunotherapy warrants further investigation. CLINICAL TRIAL INFORMATION: This clinical trial was registered with ClinicalTrials.gov identifier: NCT01847326.

A nanoengineered topical transmucosal cisplatin delivery system induces anti-tumor response in animal models and patients with oral cancer.

Despite therapeutic advancements, oral cavity squamous cell carcinoma (OCSCC) remains a difficult disease to treat. Systemic platinum-based chemotherapy often leads to dose-limiting toxicity (DLT), affecting quality of life. PRV111 is a nanotechnology-based system for local delivery of cisplatin loaded chitosan particles, that penetrate tumor tissue and lymphatic channels while avoiding systemic circulation and toxicity. Here we evaluate PRV111 using animal models of oral cancer, followed by a clinical trial in patients with OCSCC. In vivo, PRV111 results in elevated cisplatin retention in tumors and negligible systemic levels, compared to the intravenous, intraperitoneal or intratumoral delivery. Furthermore, PRV111 produces robust anti-tumor responses in subcutaneous and orthotopic cancer models and results in complete regression of carcinogen-induced premalignant lesions. In a phase 1/2, open-label, single-arm trial (NCT03502148), primary endpoints of efficacy (≥30% tumor volume reduction) and safety (incidence of DLTs) of neoadjuvant PRV111 were reached, with 69% tumor reduction in ~7 days and over 87% response rate. Secondary endpoints (cisplatin biodistribution, loco-regional control, and technical success) were achieved. No DLTs or drug-related serious adverse events were reported. No locoregional recurrences were evident in 6 months. Integration of PRV111 with current standard of care may improve health outcomes and survival of patients with OCSCC.

AL101, a gamma-secretase inhibitor, has potent antitumor activity against adenoid cystic carcinoma with activated NOTCH signaling.

Adenoid cystic carcinoma (ACC) is an aggressive salivary gland malignancy with limited treatment options for recurrent or metastatic disease. Due to chemotherapy resistance and lack of targeted therapeutic approaches, current treatment options for the localized disease are limited to surgery and radiation, which fails to prevent locoregional recurrences and distant metastases in over 50% of patients. Approximately 20% of patients with ACC carry NOTCH-activating mutations that are associated with a distinct phenotype, aggressive disease, and poor prognosis. Given the role of NOTCH signaling in regulating tumor cell behavior, NOTCH inhibitors represent an attractive potential therapeutic strategy for this subset of ACC. AL101 (osugacestat) is a potent γ-secretase inhibitor that prevents activation of all four NOTCH receptors. While this investigational new drug has demonstrated antineoplastic activity in several preclinical cancer models and in patients with advanced solid malignancies, we are the first to study the therapeutic benefit of AL101 in ACC. Here, we describe the antitumor activity of AL101 using ACC cell lines, organoids, and patient-derived xenograft models. Specifically, we find that AL101 has potent antitumor effects in in vitro and in vivo models of ACC with activating NOTCH1 mutations and constitutively upregulated NOTCH signaling pathway, providing a strong rationale for evaluation of AL101 in clinical trials for patients with NOTCH-driven relapsed/refractory ACC.

Identification of Therapeutic Targets for Amyotrophic Lateral Sclerosis Using PandaOmics - An AI-Enabled Biological Target Discovery Platform.

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease with ill-defined pathogenesis, calling for urgent developments of new therapeutic regimens. Herein, we applied PandaOmics, an AI-driven target discovery platform, to analyze the expression profiles of central nervous system (CNS) samples (237 cases; 91 controls) from public datasets, and direct iPSC-derived motor neurons (diMNs) (135 cases; 31 controls) from Answer ALS. Seventeen high-confidence and eleven novel therapeutic targets were identified and will be released onto ALS.AI (http://als.ai/). Among the proposed targets screened in the c9ALS Drosophila model, we verified 8 unreported genes (KCNB2, KCNS3, ADRA2B, NR3C1, P2RY14, PPP3CB, PTPRC, and RARA) whose suppression strongly rescues eye neurodegeneration. Dysregulated pathways identified from CNS and diMN data characterize different stages of disease development. Altogether, our study provides new insights into ALS pathophysiology and demonstrates how AI speeds up the target discovery process, and opens up new opportunities for therapeutic interventions.

The role of NSD1, NSD2, and NSD3 histone methyltransferases in solid tumors.

NSD1, NSD2, and NSD3 constitute the nuclear receptor-binding SET Domain (NSD) family of histone 3 lysine 36 (H3K36) methyltransferases. These structurally similar enzymes mono- and di-methylate H3K36, which contribute to the maintenance of chromatin integrity and regulate the expression of genes that control cell division, apoptosis, DNA repair, and epithelial-mesenchymal transition (EMT). Aberrant expression or mutation of members of the NSD family is associated with developmental defects and the occurrence of some types of cancer. In this review, we discuss the effect of alterations in NSDs on cancer patient's prognosis and response to treatment. We summarize the current understanding of the biological functions of NSD proteins, focusing on their activities and the role in the formation and progression in solid tumors biology, as well as how it depends on tumor etiologies. This review also discusses ongoing efforts to develop NSD inhibitors as a promising new class of cancer therapeutic agents.

Development and Validation of a Decision Analytical Model for Posttreatment Surveillance for Patients With Oropharyngeal Carcinoma.

Importance: Clinical practice regarding posttreatment radiologic surveillance for patients with oropharyngeal carcinoma (OPC) is neither adapted to individual patient risk nor fully evidence based. Objectives: To construct a microsimulation model for posttreatment OPC progression and use it to optimize surveillance strategies while accounting for both tumor stage and human papillomavirus (HPV) status. Design, Setting, and Participants: In this decision analytical modeling study, a Markov model of 3-year posttreatment patient trajectories was created. The training data source was the American College of Surgeon's National Cancer Database from 2010 to 2015. The external validation data set was the 2016 International Collaboration on Oropharyngeal Cancer Network for Staging (ICON-S) study. Training data comprised 2159 patients with OPC treated with primary radiotherapy who had known HPV status and disease staging information. Patients with American Joint Committee on Cancer, 7th edition stage III to IVB disease and those with clinical metastases during the time of primary treatment were included. Data were analyzed from August 1 to October 31, 2020. Main Outcomes and Measures: Main outcomes included disease stage and HPV status, specific disease transition probabilities, and latency of surveillance regimens, defined as time between recurrence incidence and disease discovery. Results: Training data consisted of 2159 total patients (1708 men [79.1%]; median age, 59.6 years [range, 40-90 years]; 401 with stage III disease, 1415 with stage IVA disease, and 343 with stage IVB disease). Cohorts predominantly had HPV-negative disease (1606 [74.4%]). With model-optimized regimens, recurrent disease was discovered a mean of 0.6 months (95% CI, 0.5-0.8 months) earlier than with a standard surveillance regimen based on current clinical guidelines. Recurrent disease was discovered using the optimized regimens without significant reduction in sensitivity. Compared with strategies based on reimbursement guidelines, the model-optimized regimens found disease a mean of 1.8 months (95% CI, 1.3-2.3 months) earlier. Conclusions and Relevance: Optimized, risk-stratified surveillance regimens consistently outperformed nonoptimized strategies. These gains were obtained without requiring any additional imaging studies. This approach to risk-stratified surveillance optimization is generalizable to a broad range of tumor types and risk factors.

Hallmarks of aging-based dual-purpose disease and age-associated targets predicted using PandaOmics AI-powered discovery engine.

Aging biology is a promising and burgeoning research area that can yield dual-purpose pathways and protein targets that may impact multiple diseases, while retarding or possibly even reversing age-associated processes. One widely used approach to classify a multiplicity of mechanisms driving the aging process is the hallmarks of aging. In addition to the classic nine hallmarks of aging, processes such as extracellular matrix stiffness, chronic inflammation and activation of retrotransposons are also often considered, given their strong association with aging. In this study, we used a variety of target identification and prioritization techniques offered by the AI-powered PandaOmics platform, to propose a list of promising novel aging-associated targets that may be used for drug discovery. We also propose a list of more classical targets that may be used for drug repurposing within each hallmark of aging. Most of the top targets generated by this comprehensive analysis play a role in inflammation and extracellular matrix stiffness, highlighting the relevance of these processes as therapeutic targets in aging and age-related diseases. Overall, our study reveals both high confidence and novel targets associated with multiple hallmarks of aging and demonstrates application of the PandaOmics platform to target discovery across multiple disease areas.

Molecular drivers of oral cavity squamous cell carcinoma in non-smoking and non-drinking patients: what do we know so far?

Oral cavity squamous cell carcinoma (OCSCC) is one of the most common head and neck cancers worldwide. It is well known that risk factors for OCSCC include tobacco and excess alcohol consumption. However, in recent years, OCSCC incidence has been increasing in patients without these traditional risk factors. The cause of this increase is unclear and various genetic, environmental, and infectious factors have been hypothesized to play a role. Additionally, there are expert opinions that oral cancer in non-smoking, non-drinking (NSND) patients have a distinct phenotype resulting in more aggressive disease presentation and poorer prognosis. In this review, we summarize the current state of knowledge for oral cavity cancer in patients without traditional risk factors.

Prospective study evaluating dynamic changes of cell-free HPV DNA in locoregional viral-associated oropharyngeal cancer treated with induction chemotherapy and response-adaptive treatment.

BACKGROUND: Human papillomavirus (HPV)-associated oropharyngeal cancer (OPC) has a favorable prognosis which has led to efforts to de-intensify treatment. Response-adaptive de-escalated treatment is promising, however improved biomarkers are needed. Quantitative cell-free HPV-DNA (cfHPV-DNA) in plasma represents an attractive non-invasive biomarker for grading treatment response and post-treatment surveillance. This prospective study evaluates dynamic changes in cfHPV-DNA during induction therapy, definitive (chemo)radiotherapy, and post-treatment surveillance in the context of risk and response-adaptive treatment for HPV + OPC. METHODS: Patients with locoregional HPV + OPC are stratified into two cohorts: High risk (HR) (T4, N3, [Formula: see text] 20 pack-year smoking history (PYH), or non-HPV16 subtype); Low risk (LR) (all other patients). All patients receive induction chemotherapy with three cycles of carboplatin and paclitaxel. LR with ≥ 50% response receive treatment on the single-modality arm (minimally-invasive surgery or radiation alone to 50 Gy). HR with ≥ 50% response or LR with ≥ 30% and < 50% response receive treatment on the intermediate de-escalation arm (chemoradiation to 50 Gy with cisplatin). All other patients receive treatment on the regular dose arm with chemoradiation to 70 Gy with concurrent cisplatin. Plasma cfHPV-DNA is assessed during induction, (chemo)radiation, and post-treatment surveillance. The primary endpoint is correlation of quantitative cfHPV-DNA with radiographic response. DISCUSSION: A de-escalation treatment paradigm that reduces toxicity without compromising survival outcomes is urgently needed for HPV + OPC. Response to induction chemotherapy is predictive and prognostic and can select candidates for de-escalated definitive therapy. Assessment of quantitative cfHPV-DNA in the context of response-adaptive treatment of represents a promising reliable and convenient biomarker-driven strategy to guide personalized treatment in HPV + OPC. TRIAL REGISTRATION: This trial is registered with ClinicalTrials.gov on October 1st, 2020 with Identifier: NCT04572100 .

Application of liquid biopsy as multi-functional biomarkers in head and neck cancer.

Head and neck squamous cell carcinoma (HNSCC) is a molecularly heterogeneous disease, with a 5-year survival rate that still hovers at ~60% despite recent advancements. The advanced stage upon diagnosis, limited success with effective targeted therapy and lack of reliable biomarkers are among the key factors underlying the marginally improved survival rates over the decades. Prevention, early detection and biomarker-driven treatment adaptation are crucial for timely interventions and improved clinical outcomes. Liquid biopsy, analysis of tumour-specific biomarkers circulating in bodily fluids, is a rapidly evolving field that may play a striking role in optimising patient care. In recent years, significant progress has been made towards advancing liquid biopsies for non-invasive early cancer detection, prognosis, treatment adaptation, monitoring of residual disease and surveillance of recurrence. While these emerging technologies have immense potential to improve patient survival, numerous methodological and biological limitations must be overcome before their implementation into clinical practice. This review outlines the current state of knowledge on various types of liquid biopsies in HNSCC, and their potential applications for diagnosis, prognosis, grading treatment response and post-treatment surveillance. It also discusses challenges associated with the clinical applicability of liquid biopsies and prospects of the optimised approaches in the management of HNSCC.

A robust and interpretable gene signature for predicting the lymph node status of primary T1/T2 oral cavity squamous cell carcinoma.

Oral cavity squamous cell carcinoma (OSCC) affects more than 30 000 individuals in the United States annually, with smoking and alcohol consumption being the main risk factors. Management of early-stage tumors usually includes surgical resection followed by postoperative radiotherapy in certain cases. The cervical lymph nodes (LNs) are the most common site for local metastasis, and elective neck dissection is usually performed if the primary tumor thickness is greater than 3.5 mm. However, postoperative histological examination often reveals that many patients with early-stage disease are negative for neck nodal metastasis, posing a pressing need for improved risk stratification to either avoid overtreatment or prevent the disease progression. To this end, we aimed to identify a primary tumor gene signature that can accurately predict cervical LN metastasis in patients with early-stage OSCC. Using gene expression profiles from 189 samples, we trained K-top scoring pairs models and identified six gene pairs that can distinguish primary tumors with nodal metastasis from those without metastasis. The signature was further validated on an independent cohort of 35 patients using real-time polymerase chain reaction (PCR) in which it achieved an area under the receiver operating characteristic (ROC) curve and accuracy of 90% and 91%, respectively. These results indicate that such signature holds promise as a quick and cost effective method for detecting patients at high risk of developing cervical LN metastasis, and may be potentially used to guide the neck treatment regimen in early-stage OSCC.