Osteonecrosis of the jaw: a rare but possible side effect in thyroid cancer patients treated with tyrosine-kinase inhibitors and bisphosphonates

Exploring the Impact of Novel Anti-Cancer Therapies on Jaw Osteonecrosis and Other Bones: A Comprehensive Review

Osteonecrosis is a debilitating condition characterized by the loss of blood supply to the bones, leading to bone death. This condition can impact various bones, including the jaw, which significantly affects patients' quality of life by causing difficulties in swallowing, feeding, chewing, and speaking, along with swollen, painful mucous membranes and chronic sinusitis. Osteonecrosis can arise due to treatment with antiresorptive drugs. However, there is a growing number of reports of osteonecrosis following novel targeted anti-cancer treatments, such as tyrosine kinase inhibitors (TKIs) and biological therapies. The pathogenesis of osteonecrosis is linked to the side effects of the antiangiogenic mechanisms of these medications, leading to a disrupted blood flow. Our review aims to examine recent insights into osteonecrosis triggered by new anti-cancer drugs. Most reports focus on the osteonecrosis of the jaw (ONJ); however, we discovered that some authors have described cases of osteonecrosis affecting the femoral head or elbow following novel anti-cancer treatments. Prevention is a key component in managing osteonecrosis. Therefore, a comprehensive risk assessment should always be performed before and during anti-cancer therapy.

Tumor-associated macrophages as a potential therapeutic target in thyroid cancers

Macrophages are important precursor cell types of the innate immune system and bridge adaptive immune responses through the antigen presentation system. Meanwhile, macrophages constitute substantial portion of the stromal cells in the tumor microenvironment (TME) (referred to as tumor-associated macrophages, or TAMs) and exhibit conflicting roles in the development, invasion, and metastasis of thyroid cancer (TC). Moreover, TAMs play a crucial role to the behavior of TC due to their high degree of infiltration and prognostic relevance. Generally, TAMs can be divided into two subgroups; M1-like TAMs are capable of directly kill tumor cells, and recruiting and activating other immune cells in the early stages of cancer. However, due to changes in the TME, M2-like TAMs gradually increase and promote tumor progression. This review aims to discuss the impact of TAMs on TC, including their role in tumor promotion, gene mutation, and other factors related to the polarization of TAMs. Finally, we will explore the M2-like TAM-centered therapeutic strategies, including chemotherapy, clinical trials, and combinatorial immunotherapy.

Radio-iodine refractory thyroid cancer patients: a tailored follow-up based on clinicopathological features

OBJECTIVE

To report the experience of a single center for the selection of radioiodine-refractory (RAIR) thyroid cancer patients (RAIR-TC) who needed tyrosine kinase inhibitor (TKIs) treatment.

PATIENTS AND METHODS

We evaluated all features of 279 RAIR-TC patients both at the time of diagnosis and at the RAIR diagnosis.

RESULTS

Ninety-nine patients received indication to TKIs (Group A), while 180 remained under active surveillance (Group B). Group A had greater tumor size, more aggressive histotype, more frequent macroscopic extrathyroidal extension, distant metastases, advanced AJCC stage, and higher ATA risk of recurrence. After RAIR diagnosis, 93.9% of Group A had progression of disease (PD) after which TKIs' therapy was started. The remaining 6.1% of patients had a so severe disease at the time of RAIR diagnosis that TKIs' therapy was immediately started. Among Group B, 42.7% had up to 5 PD, but the majority underwent local treatments. The mean time from RAIR diagnosis to the first PD was shorter in Group A, and the evidence of PD within 25 months from RAIR diagnosis was associated with the decision to start TKIs.

CONCLUSIONS

According to our results, a more tailored follow-up should be applied to RAIR-TC patients. A too strict monitoring and too many imaging evaluations might be avoided in those with less-aggressive features and low rate of progression. Conversely, RAIR-TC with an advanced stage at diagnosis and a first PD occurring within 25 months from RAIR diagnosis would require a more stringent follow-up to avoid a late start of TKIs.

Adrenal insufficiency in thyroid cancer patients treated with tyrosine kinase inhibitors and detected by ACTH stimulation test

PURPOSE

Advanced thyroid cancer patients treated with tyrosine kinase inhibitors (TKI) can develop several adverse events (AEs), including adrenal insufficiency (AI).

METHODS

We studied 55 patients treated with TKI for radioiodine-refractory or medullary thyroid cancer. The adrenal function was evaluated during follow-up by performing serum basal ACTH, and basal and ACTH-stimulated cortisol.

RESULTS

Twenty-nine/55 (52.7%) patients developed subclinical AI during TKI treatment as demonstrated by a blunted cortisol response to ACTH stimulation. All cases showed normal values of serum sodium, potassium and blood pressure. All patients were immediately treated, and none showed an overt AI. Cases with AI were all negative for adrenal antibodies and did not show any adrenal gland alteration. Other causes of AI were excluded. The onset time of the AI, as measured in the subgroup with a first negative ACTH test, was < 12 months in 5/9 (55.6%), between 12 and 36 months in 2/9 (22.2%) and > 36 months in 2/9 (22.2%) cases. In our series, the only prognostic factor of AI was the elevated, although moderate, basal level of ACTH when the basal and stimulated cortisol were still normal. The glucocorticoid therapy improved fatigue in most patients.

CONCLUSIONS

Subclinical AI can be developed in > 50% of advanced thyroid cancer patients treated with TKI. This AE can develop in a wide period ranging from < 12 to > 36 months. For this reason, AI must be looked for throughout the follow-up to be early recognized and treated. A periodic ACTH stimulation test, every 6-8 months, can be helpful.

Management of Progressive Radioiodine-Refractory Thyroid Carcinoma: Current Perspective

Patients with thyroid cancer (TC) usually have an excellent prognosis; however, 5-10% of them develop an advanced disease. The prognosis of this subgroup is still favourable if the lesions respond to radioactive iodine (RAI) treatment. Nearly two-thirds of advanced TC patients become RAI-refractory (RAI-R), and their management is challenging. A multidisciplinary approach in the context of a tumour board is essential to define a personalized strategy. Systemic therapy is not always the best option. In case of slow neoplastic growth and low tumour burden, active surveillance may represent a valuable choice. Local approaches might be considered if the disease progression is limited to a single or few lesions, also in combination and during systemic therapy. Antiresorptive treatment may be started in presence of bone metastases. In case of rapid and/or symptomatic progression involving multiple lesions and/or organs, systemic therapy has to be considered, in absence of contraindications. The multi-kinase inhibitors (MKIs) lenvatinib and sorafenib are currently available as first-line treatment for advanced progressive RAI-R TC. Among second-line options, cabozantinib has been recently approved in RAI-R TC who progressed during MKIs targeting the vascular endothelial growth factor receptor (VEGFR). In the last few years, next-generation sequencing (NGS) assays have been increasingly employed, permitting identification of the genetic alterations harboured by TC, with a significant impact on patients' management. Novel selective targeted therapies have been introduced for the treatment of RAI-R TC in selected cases: REarranged during Transfection (RET) inhibitors (selpercatinib and pralsetinib) and Tropomyosin Receptor Kinase (TRK) inhibitors (larotrectinib and entrectinib) have recently expanded the panorama of the therapeutic options. Moreover, immune checkpoint inhibitors (ICIs) have shown promising results, and they are still under investigation.

On-Target Side Effects of Targeted Therapeutics of Cancer

The concept of precision medicine is based on the identification of hallmarks of cancer to exploit them as drug targets. The basic idea was that in this way the therapeutic modalities will be more effective and the side effects will be less. Since the majority of these novel modalities are not specific for a cancer-related biological process or a cancer-specific (mutant) target protein, it is not a surprise that we had to learn new type of side effects, because these therapeutics also affect physiological or pathological processes. Even more, in cases of some of these novel therapies we were able to discover new molecular mechanisms of physiological and pathological processes. Identification of the on-target side effects of targeted drugs can help to prevent the development of them or better manage the patients when emerge during cancer therapy.

Bioinformatic Data Mining for Candidate Drugs Affecting Risk of Bisphosphonate-Related Osteonecrosis of the Jaw (BRONJ) in Cancer Patients

Background. Bisphosphonate-related osteonecrosis of the jaw (BRONJ) leads to significant morbidity. Other coadministered drugs may modulate the risk for BRONJ. The present study aimed to leverage bioinformatic data mining to identify drugs that potentially modulate the risk of BRONJ in cancer. Methods. A GEO gene expression dataset of peripheral blood mononuclear cells related to BRONJ in multiple myeloma patients was downloaded, and differentially expressed genes (DEGs) in patients with BRONJ versus those without BRONJ were identified. A protein-protein interaction network of the DEGs was constructed using experimentally validated interactions in the STRING database. Overrepresented Gene Ontology (GO) molecular function terms and KEGG pathways in the network were analysed. Network topology was determined, and ‘hub genes’ with degree ≥2 in the network were identified. Known drug targets of the hub genes were mined from the ‘drug gene interaction database’ (DGIdb) and labelled as candidate drugs affecting the risk of BRONJ. Results. 751 annotated DEGs ( $\log \text{FC}\ge 1.5$ , $p<0.05$ ) were obtained from the microarray gene expression dataset GSE7116. A PPI network with 633 nodes and 168 edges was constructed. Data mining for drugs interacting with 49 gene nodes was performed. 37 drug interactions were found for 9 of the hub genes including TBP, TAF1, PPP2CA, PRPF31, CASP8, UQCRB, ACTR2, CFLAR, and FAS. Interactions were found for several established and novel anticancer chemotherapeutic, kinase inhibitor, caspase inhibitor, antiangiogenic, and immunomodulatory agents. Aspirin, metformin, atrovastatin, thrombin, androgen and antiandrogen drugs, progesterone, Vitamin D, and Ginsengoside 20(S)-Protopanaxadiol were also documented. Conclusions. A bioinformatic data mining strategy identified several anticancer, immunomodulator, and other candidate drugs that may affect the risk of BRONJ in cancer patients.