Carcinogenesis is a multistep process that consists of the transformation of healthy cells into cancer cells. Such an alteration goes through various stages and is closely linked to random mutations of genes that have a key role in the neoplastic phenotype. During carcinogenesis, cancer cells acquire and exhibit several characteristics including sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, activating invasion and metastasis, and expressing an immune phenotype, which allow them to evade recognition and destruction through cognate immune cells. In addition, cancer cells may acquire the ability to reprogram their metabolism in order to further promote growth, survival, and energy production. This phenomenon, termed metabolic reprogramming, is typical of all solid tumors, including squamous carcinomas of the head and neck (SCCHN). In this review, we analyze the genetic and biological mechanisms underlying metabolic reprogramming of SCCHN, focusing on potential therapeutic strategies that are able to counteract it.

Checkpoint inhibitors (ICIs) have demonstrated substantial efficacy in the treatment of numerous solid tumors, including head and neck cancer. Their inclusion in the therapeutic paradigm in metastatic lines of treatment has certainly improved the outcomes of these patients. Starting from this assumption, numerous studies have been conducted on ICIs in other earlier disease settings, including studies conducted in patients in neoadjuvant settings. However, how many and which studies are truly significant? Can they lay concrete foundations for further future studies and therefore allow us to continue to have this interesting future perspective? Through a review of the existing literature, coupled with insights gleaned from clinical practice and from the main recently published studies, we aim to examine the therapeutic potential of ICIs in patients affected by head and neck cancer in a neoadjuvant treatment setting and encourage researchers to set up successful future clinical trials.

Chemical, physical, and infectious agents may induce carcinogenesis, and in the latter case, viruses are involved in most cases. The occurrence of virus-induced carcinogenesis is a complex process caused by an interaction across multiple genes, mainly depending by the type of the virus. Molecular mechanisms at the basis of viral carcinogenesis, mainly suggest the involvement of a dysregulation of the cell cycle. Among the virus-inducing carcinogenesis, Epstein Barr Virus (EBV) plays a major role in the development of both hematological and oncological malignancies and importantly, several lines of evidence demonstrated that nasopharyngeal carcinoma (NPC) is consistently associated with EBV infection. Cancerogenesis in NPC may be induced by the activation of different EBV “oncoproteins” which are produced during the so called “latency phase” of EBV in the host cells. Moreover, EBV presence in NPC does affect the tumor microenvironment (TME) leading to a strongly immunosuppressed status. Translational implications of the above-mentioned statements are that EBV-infected NPC cells can express proteins potentially recognized by immune cells in order to elicit a host immune response (tumor associated antigens). Three immunotherapeutic approaches have been implemented for the treatment of NPC including active, adoptive immunotherapy, and modulation of immune regulatory molecules by use of the so-called checkpoint inhibitors. In this review, we will highlight the role of EBV infection in NPC development and analyze its possible implications on therapy strategies.

Salivary gland carcinomas (SGCs) are rare neoplasms, representing less than 10% of all head and neck tumors, but they are extremely heterogeneous from the histological point of view, their clinical behavior, and their genetics. The guidelines regarding their treatment include surgery in most cases, which can also play an important role in oligometastatic disease. Where surgery cannot be used, systemic therapy comes into play. Systemic therapy for many years has been represented by polychemotherapy, but recently, with the affirmation of translational research, it can also count on targeted therapy, at least in some subtypes of SGCs. Interestingly, in some SGC histotypes, predominant mutations have been identified, which in some cases behave as “driver mutations”, namely mutations capable of governing the carcinogenesis process. Targeting these driver mutations may be an effective therapeutic strategy. Nonetheless, it is not always possible to have drugs suitable for targeting driver mutations—and targeting driver mutations is not always accompanied by a clinical benefit. In this review, we will analyze the main mutations predominant in the various histotypes of SGCs.

Background: Pain remains one of the most debilitating and prevalent symptoms in cancer patients. However, assessment based solely on subjective self-report tools is limited by cognitive impairment and the heterogeneous nature of cancer pain. Since evidence on the ability of physiological biosignals to discriminate cancer pain intensity and pain phenotypes in real clinical settings remains limited, this study explored the potential of biosignals to discriminate between pain intensity and pain type. Methods: Electrodermal activity (EDA) and electrocardiogram (ECG) signals were recorded in cancer patients using the BITalino (r)evolution board (sampling frequency 1000 Hz). EDA was processed to extract skin conductance responses (SCRs) using continuous decomposition analysis (CDA) and trough-to-peak (TTP) methods. Heart rate variability (HRV) features were extracted in both time and frequency domains, including low frequency (LF), high frequency (HF), and the LF/HF ratio. Non-parametric Kruskal–Wallis tests were performed to compare biosignal parameters across pain intensity (Numeric Rating Scale, NRS: low 1–3; medium 4–6; and high 7–10) and pain types (nociceptive, neuropathic, mixed, and breakthrough cancer pain—BTCP). Results: Data from 61 patients were analyzed. For EDA, the maximum skin conductance response amplitude (MaxCDA) significantly differed across intensity groups (p = 0.037). Post hoc analysis showed a significant difference between the low- and high-intensity groups (p = 0.015), with the low-intensity group exhibiting a higher mean MaxCDA (0.063 µS) than the high-intensity group (0.024 µS). Several EDA parameters were significantly associated with pain type. The number of SCRs (TTP) (p = 0.015) and maximum SCR amplitude (TTP) (p = 0.040) were significantly lower in the mixed pain group compared with the nociceptive and neuropathic groups. No HRV parameters showed significant associations with pain intensity or pain type. BTCP did not significantly affect any biosignal parameters. Subgroup analyses showed that EDA features discriminating mixed pain were preserved in patients without bone metastases, BTCP, or high opioid burden, whereas no clinical variable modified the association between biosignals and pain intensity and type. Conclusions: In this investigation, selected EDA parameters were associated with cancer pain intensity and pain type, whereas heart rate variability measures did not show significant discrimination under the present methodological conditions. These findings suggest that EDA may provide complementary information on pain-related autonomic alterations in oncology patients. However, biosignals should not be considered standalone indicators of pain, and their interpretation requires integration with clinical variables and pharmacological context. Further studies adopting multimodal and longitudinal approaches are needed to clarify their role in automatic pain assessment in cancer care.

Neoadjuvant strategies in head and neck squamous cell carcinoma (HNSCC) are reshaping therapeutic paradigms by shifting emphasis from anatomical staging toward biology-driven response stratification. The transition from induction chemotherapy to immune checkpoint–based and combination regimens has transformed the perioperative setting into a translational platform that enables interrogation of tumor–immune interactions and clonal selection under therapeutic pressure prior to surgery. In this context, pathological response assessment has emerged as a robust surrogate endpoint, overcoming the limitations of radiologic evaluation, which often fails to capture immune-mediated pseudoprogression and spatially heterogeneous regression. Quantification of residual viable tumor (RVT) provides a reproducible metric of therapeutic efficacy, while characterization of immune-related regression beds, tertiary lymphoid structures, macrophage polarization states, and compartment-specific nodal responses offers mechanistic insight into tumor clearance and resistance evolution. Evidence from phase II trials, single-cell sequencing, spatial transcriptomics, and multiplex immune profiling supports the prognostic relevance of pathology-driven endpoints. Integration of digital pathology and artificial intelligence–assisted image analysis further enhances reproducibility and enables high-resolution mapping of residual disease and immune architecture. Within this modern oncologic framework, the neoadjuvant-treated specimen functions as a dynamic biomarker platform guiding response-adapted surgical strategies and biomarker-driven clinical trial design. This study was designed as a narrative review. A structured literature search was performed using PubMed and major oncology journals to identify relevant studies on pathology-driven response assessment in neoadjuvant-treated head and neck squamous cell carcinoma. The review focused on publications addressing histopathological response criteria, immune microenvironment remodeling, spatial profiling technologies, and computational pathology approaches.