Role of radiation therapy for renal tumors

Intraoperative Cryotherapy in the Treatment of Metastatic Renal Cell Carcinoma of the Bone

Osseous metastases in renal cell carcinoma (RCC) are a heterogeneous mix of cells with hypervascular and rapidly destructive properties that frequently exhibit resistance to both radiation and chemotherapy. Despite this, some patients with isolated and oligometastatic disease have the potential to be cured. Regardless, aggressive metastatic control is critical to minimizing morbidity and mortality for all patients with metastatic RCC. Percutaneous cryoprobes were developed as a minimally invasive technique for both pain relief and tumor control. However, there is little evidence describing an alternative use of this technology in the operating room to assist with open tumor resections, and no formal role for its use in orthopedics exists. Therefore, the authors added this modality to their intraoperative treatment of osseous RCC to investigate whether it would influence their ability to obtain local metastatic control. The authors performed a retrospective chart review of prospectively obtained data to evaluate the role of intraoperative cryotherapy in the treatment of osseous RCC. From 2004 to 2017, cryotherapy was used in 43 procedures, alleviating the need for additional radiation 84% (36 of 43) of the time. Local tumor control was achieved in 100% (43 of 43) of cases. There were 2 wound-related complications and 1 pathologic fracture. Despite the study's limitations, the authors believe that cryotherapy contributed to the reliability and reproducibility of their intralesional resections. Given the palliative, and potentially curative, opportunities afforded by complete locoregional tumor control, the authors support further investigation into the use of intraoperative cryotherapy to treat osseous metastases secondary to RCC. [Orthopedics. 2021;44(5):e645-e652.].

The Therapeutic Landscape of Renal Cell Carcinoma: From the Dark Age to the Golden Age

Oncologic treatments for renal cell carcinoma (RCC) have undergone a major revolution in the past 2 decades, moving away from the pre-2004 Dark Age during which interleukin 2 and interferon-α were the only therapeutic options and induced treatment responses in only 5% to 10% of patients with metastatic disease. The development of anti-angiogenic tyrosine kinase inhibitors against vascular endothelial growth factor receptor 2 and inhibitors of mammalian target of rapamycin complex 1 in 2005 introduced the Modern Age with better overall and progression-free survival and a greater number of patients (30%-40%) responding to and (∼80%) benefiting from these targeted therapeutic agents. The coming of age of the immuno-oncology era with the use of immune checkpoint inhibitors (ICIs) have ushered us into the Golden Age of metastatic RCC care, in which combined administrations of two ICIs (anti-programmed cell death protein 1/programmed death-ligand 1 and anti-cytotoxic T-lymphocyte-associated protein 4 or one tyrosine kinase inhibitor plus one ICI (anti-programmed cell death protein 1/programmed death-ligand 1) have recast the treatment landscape of clear cell RCC, the most common RCC subtype, with an approximately 60% response rate and an approximately 90% disease control rate that further improves metastatic RCC survival. Exciting clinical trials are in the pipeline investigating complementary/synergistic molecular mechanisms, based on studies investigating the biology, pathology, and genomics of renal carcinoma and the respective treatment outcome. This will enable us to enter the Diamond Age of precision medicine in which a specific treatment can be tailored to the specific biological and pathologic circumstance of an individual kidney tumor to offer more effective yet less toxic therapy.

Outcomes of Artificial Intelligence Volumetric Assessment of Kidneys and Renal Tumors for Preoperative Assessment of Nephron Sparing Interventions

Background Renal cell carcinoma is the most common kidney cancer and the 13th most common cause of cancer death worldwide. Partial nephrectomy and percutaneous ablation, increasingly utilized to treat small renal masses and preserve renal parenchyma, require precise preoperative imaging interpretation. We sought to develop and evaluate a convolutional neural network (CNN), a type of deep learning artificial intelligence, to act as a surgical planning aid by determining renal tumor and kidney volumes via segmentation on single-phase computed tomography (CT). Materials and Methods After institutional review board approval, the CT images of 319 patients were retrospectively analyzed. Two distinct CNNs were developed for (1) bounding cube localization of the right and left hemi-abdomen and (2) segmentation of the renal parenchyma and tumor within each bounding cube. Training was performed on a randomly selected cohort of 269 patients. CNN performance was evaluated on a separate cohort of 50 patients using Sorensen-Dice coefficients (which measures the spatial overlap between the manually segmented and neural network derived segmentations) and Pearson correlation coefficients. Experiments were run on a GPU-optimized workstation with a single NVIDIA GeForce GTX Titan X (12GB, Maxwell architecture). Results Median Dice coefficients for kidney and tumor segmentation were 0.970 and 0.816, respectively; Pearson correlation coefficients between CNN-generated and human-annotated estimates for kidney and tumor volume were 0.998 and 0.993 (p < 0.001), respectively. End-to-end trained CNNs were able to perform renal parenchyma and tumor segmentation on a new test case in an average of 5.6 seconds. Conclusions Initial experience with automated deep learning artificial intelligence demonstrates that it is capable of rapidly and accurately segmenting kidneys and renal tumors on single-phase contrast-enhanced CT scans and calculating tumor and renal volumes.

Metastatic clear cell renal cell carcinoma presenting as breast lump: A rare case report

Renal cell carcinoma is as an aggressive tumor associated with metastasis in about one-third of the cases, but it rarely metastasizes to breast, which further is a rare site of metastasis from extramammary solid tumors. Here, we report the case of a 60-year-old female who presented with breast metastasis from renal cell carcinoma. The mammogram showed a well-defined hyperdense mass of 2.5 × 2.7 cm with microlobulated margins. The mass was hypervascular on ultrasound. Further, contrast enhanced computed tomography (CECT) abdomen revealed a 6.3 × 6.0 × 6.2 cm mass arising from the middle and the lower pole of right kidney. Fine-needle aspiration cytology (FNAC) of the right breast lump, along with cellblock preparation from the aspirated material and immunohistochemistry (IHC) on the cellblock was performed. The tumor was positive for pan-cytokeratin, vimentin, and CD10, while the markers for primary breast carcinoma were negative. On the basis of morphology and IHC, the final diagnosis of the breast mass was metastatic clear cell renal cell carcinoma. This case highlights the importance of ruling out possibility of metastasis in cases of breast mass. The correct diagnosis of these cases is crucial since the mastectomy is not required. Here, we discuss the radiological and morphological features on cytology and cellblock of this rare case of breast metastasis from renal cell carcinoma.

Exploiting natural anti-tumor immunity for metastatic renal cell carcinoma

Clinical observations of spontaneous disease regression in some renal cell carcinoma (RCC) patients implicate a role for tumor immunity in controlling this disease. Puzzling, however, are findings that high levels of tumor infiltrating lymphocytes (TIL) are common to RCC. Despite expression of activation markers by TILs, functional impairment of innate and adaptive immune cells has been consistently demonstrated contributing to the failure of the immune system to control RCC. Immunotherapy can overcome the immunosuppressive effects of the tumor and provide an opportunity for long-term disease free survival. Unfortunately, complete response rates remain sub-optimal indicating the effectiveness of immunotherapy remains limited by tumor-specific factors and/or cell types that inhibit antitumor immune responses. Here we discuss immunotherapies and the function of multiple immune system components to achieve an effective response. Understanding these complex interactions is essential to rationally develop novel therapies capable of renewing the immune system's ability to respond to these tumors.