A multi-site cutting device implements efficiently the divide-and-conquer strategy in tumor sampling

Introduction

In the light of current findings provided by numerous sequencing tools, it is known that practically all human neoplasms display some degree of intratumor heterogeneity (ITH)¹. Characteristically, ITH is not uniformly distributed along the tumor; instead, it shows a regional distribution following a stochastic pattern, the final result being unique, unpredictable, and dynamically varying along the time². The correct identification of ITH is mandatory now that targeted therapies are offering promising results to patients³, but pathologists - the specialists in charge of tumor selection for analysis - seem to have not given, so far, an appropriate answer to this issue.

We have recently proposed a reliable, affordable and time-saving solution to this problem⁴. The goal is twofold; to improve ITH detection and to perform ITH at affordable laboratory costs. This simple solution is based on the divide-and-conquer algorithm (DAC). Noteworthy, tumor sampling following DAC outperforms the routine protocol sampling for identifying ITH and, it does it, at a similar cost⁴. However, pathologists could consider that DAC is a time-consuming method when grossing, which might make it difficult to introduce it in routine practice. In this brief report, we describe a simple procedure to overcome this problem.

Method and results

The so-called DAC algorithm⁵ is based on recursively breaking down a problem in smaller parts (divide) until these are simple enough to be solved directly (conquer). Then, partial solutions are combined to solve the original problem. DAC strategies have been largely applied in science to solve complex problems, including several challenging issues in biomedical areas. As early as in 1967, DAC helped clinicians to correlate hypoglycemia with infantile convulsions⁶. In addition, DAC has been useful in cell biology and oncology, for instance in selecting the appropriate cells for biological experiments⁷ and, more recently, in helping to decipher breast cancer heterogeneity⁸.

Here DAC is applied to clear cell renal cell carcinomas (ccRCCs), since these tumors are frequently large and, for this reason, impossible to be totally sampled. Any other large tumor, however, can benefit from this method. The DAC strategy (Figure 1) requires the pathologist to select, instead of a few large fragments, a substantial number of small ones widely distributed along the entire tumor. However, pathologists under a daily routine pressure can perceive this method as laborious and time-consuming.

Figure 1. Schematic representation of routine (left) and divide-and-conquer (right) strategies in tumor sampling.

A simple device consisting of a cutting grid (here, a potato cutter) will overcome this inconvenience. When applied directly to the whole tumor surface previously thin-sliced, the grid will cut it into small cubes in one shot (Figure 2). Next, the pathologist’s decision will consist simply in selecting the cubes that will be processed for analysis as previously reported⁴. The method can be applied (and has been tested) to both fresh and formalin-fixed tissue, saves time, and assures a uniform sampling distribution along the tumor. The objective for improving efficiency of targeted therapies is the discovery of the complete ITH spectrum, and not its exact location. Thus the selected cubes included in the cassettes (six to eight cubes per cassette) will provide much more thorough information of the tumor, both under the microscope as well as at the molecular level.

Figure 2. Tumor tissue sampling after being divided with a cutting grid.

Discussion

The use of the DAC method to help sampling strategies is not new. Indeed some authors have applied the algorithm in particle physics to improve the diffusion sampling in generalized ensemble simulations⁹. This approach, or any other with scientific basis, has not been implemented for tissue selection in Pathology laboratories so far, since the pathologists did not consider tumor sampling a complex problem in the pre-molecular era.

An experience-based reasoning says that this option will save pathologist’s time when handling large tumors, in a manner which is inexpensive and reliable at the same time. In combination with the changes proposed for the technician training in our previous report⁴, this new alternative will make the pathologists’ routine much faster and robust providing an integrated solution to fulfill basic researchers’ expectations¹⁰. If the DAC strategy is adopted as a suitable method to increase the amount of information given to oncologists, pathologist's routine will move from the classic big-fragments-into-the-cassette routine to a sort of rudimentary tissue microarray building, as recently proposed⁴.

Figures are demonstrative. For instance, the DAC strategy applied to a ccRCC of 10 cm in diameter - a quite common situation in routine pathology - will generate approximately 80 small samples (of about 4–5 mm in size) that would be included in 10 cassettes for a thorough tumor examination. Importantly to remark, the same 10 cm in diameter tumor would need also 10 cassettes for the analysis, with one tumor sample per cassette, in the case of routine sampling protocols¹¹.

Depending on the pathologist’s skills, the time to collect 80 small samples in the grossing room is variable, but in any case, long. For this reason, any successful alternative must necessarily overcome this hurdle. A feasible choice would be an electric bacon slicer, but a long bladed knife will also work. To note, slicing electric machines are being increasingly used in pathology for handling radical prostatectomies¹² and other surgical specimens¹³, and they are the first step in the whole-mounting processing for tumor mapping. In this case, the obtained ccRCC slices can be quickly cut in one shot by pressing on the entire tumor surface with a cutting grid. The procedure will generate many cubes ready to be included within a cassette. If we assume that tumor sampling following a DAC strategy is appropriate for improving ITH detection, the use of a cutting grid will shorten significantly the total process ensuring a uniform and widespread selection of the samples. A straightforward estimation with some practical cases indicates that the time for obtaining 80 samples with this method is reduced to a tenth as we cut 10 small tumor pieces at the same time.

Conclusions

The present paper describes a new method for tumor sampling in routine pathology inspired by the DAC algorithm⁴. Once DAC has been proved to be efficient for ITH detection, we expect that the use of a cutting grid will make affordable its widespread application. Objectives are twofold: ITH detection improvement and time optimization (cost) in Pathology laboratories.